Tootfinder

Bin jetzt auf der Zugfahrt endlich dazu gekommen, das Buch fertigzulesen. @…'s "Die Verkrempelung der Welt" ist ein Buch, welches einem diffusen Gefühl einen Namen, eine Struktur gibt. Und auch noch sehr unterhaltsam geschrieben. Empfehlung

U.S. health officials have changed their advice to international travelers about measles,
saying that Americans should be vaccinated against the virus
-- no matter where they’re going.
U.S. residents are recommended to get measles-mumps-rubella shots, anyway.
But the Centers for Disease Control and Prevention previously emphasized the importance of vaccination for travelers going to countries with outbreaks.

All international travelers should get measles vaccinations, CDC says
U.S. health officials have changed their advice to international travelers about measles, saying Americans should be vaccinated against the disease no matter where they travel in the world. U.S. residents are recommended to get measles-mumps-rubella shots, anyway. But the Centers for Disease Control and Prevention previously emphasized the importance of vaccination for travelers going to countries with outbreaks. Last week, the CDC updated its guidance to call for vaccinations for travelers goi…

Trump uses Propecia for hair loss...
"His genitals shrank and changed shape" - National Zero
https://nationalzero.com/2025/06/02/his-genitals-shrank-and-changed-shape/

the existence of mousegirls implies the existence of keyboardgirls

@… I know that google docs can export markdown (but I’ve never built something with it, for the record)

Just investigated the app myself. It wants “always” location permissions, which is concerning. I’d like a bit more trust and accountability from the developer before enabling that.
Left it on my phone, and will enable location tracking if and when I make a report.

This is a good account of the ham-fisted use of AI in the MAHA report. AI has no understanding of science, and if it does get something right, it's because of the (human) choice of training materials. It's undisclosed use is dangerous and dishonest -like RFK Jr
https://www.washing…

White House MAHA Report may have garbled science by using AI, experts say
The report, led by Health and Human Services Secretary Robert F. Kennedy Jr., was intended to address the reasons for the decline in Americans’ life expectancy.

My Mac ran out of disk space (1 TB). Which felt … a bit weird and unexpected. So I opened up GrandPerspective to have a look…
Oh wait, what’s that?
/Users/matthiasott/Library/Caches/Adobe/AfterEffects is taking up how much space?
317G?!? 😅
That’s a lot of cache!

I downloaded a bunch of podcasts before leaving Italy. An unexpected consequence is that I'm still getting hit with ads in Italian. AmEx and Shopify come really hard at you! #Italy25

While on my bike ride this morning I saw @… with some other runners (well, they were standers at the time) and that was pretty cool.

Happy start of the hurricane season, I guess.

Initial default PCB layout for the switch engine board.
Surprisingly simple, the UltraRAM means I should be able to keep the entire switch's buffering on chip and not need any external RAM. So most of the HP I/Os are completely unused.

Valt morgen het kabinet #Schoof ?

On top of all of this there's a meta-effect: a certain class of their best engineers want no part of this and have left. The people with the peak insight that simplify things and unify products into cohesive, useful systems are leaving.

Tralalero Tralala and Bombardino Crocodilo memes have been accused of being Islamophobic, as lyrics of the former's video mock Allah in Italian, although some Italian users have pointed out that it is merely generic blasphemy.

wandklexe ahoi!
#Kundenglücklichmachungsposteinlieferungsgeräusch

We're so desperate to envision some form of justice for all the wrongs they've committed, it's easier to envision alt-right MAGA freaks as a cult, inevitably fated to eat itself & die.
☑️ The Real Reason We Want to See MAGA as a Cult | The New Republic
https://newrepublic.com/ar…

The Real Reason We Want to See MAGA as a Cult
Understanding Trump’s movement this way helps us believe it will come to some disastrous end.

"UK must consider food and climate part of national security, say top ex-military figures"
#UK #UnitedKingdom #Climate

Traveling on a Swiss train while listening to The Chemical Brothers' "Star Guitar" is like being in the actual videoclip https://www.youtube.com/watch?v=0S43IwBF0uM

Looks like it wouldn’t be too hard for ICE to tap the Flock cameras increasingly deployed around SF, if they aren’t already, by asking either SFPD or other PDs it shares access with to do the searches for them
https://www.404media.co/ice-taps-into-nati

ICE Taps into Nationwide AI-Enabled Camera Network, Data Shows
Flock's automatic license plate reader (ALPR) cameras are in more than 5,000 communities around the U.S. Local police are doing lookups in the nationwide system for ICE.

If you were to search for 🌈 in just the right place, you might find a #PrideMonth surprise in your favourite browser. 😉

#pastpuzzle 328
🟩🟩🟨🟥 ( 6)
🟩🟩🟥🟩 ( 10)
🟩🟩🟩🟩 (0)
▪️▪️▪️▪️
3/4 🥉
https://www.pastpuzzle.de

Look, I can sell you the organ and the grinder, but you'll have to supply your own monkey.

Trotz wachsender #Wettbewerbsfähigkeit von #Solarenergie und #Batteriespeichern diskutieren deutsche

If an "undercover" officer is seen and known to the press then I would not hesitate to publish their face image and identity - in part because they have failed actually be "undercover".
That said, the fact that agents can't be identified as actual Federal agents, much less identified down to the individual actor when they do ill, is simply unacceptable.
TSA at least has numbers on their "name" badges, so one can make a complaint about a person …

The ICE agents disappearing your neighbors would like a little privacy, please
After taking four people into custody at SF’s immigration court, ICE wanted The Standard to conceal agents’ faces.

It should be bedtime for me, but as I had a nap earlier, I am now 100% alert 😅
The only reason I had to nap earlier was because of the anti-histamines I had yesterday messing with my sleeping patterns.

I disse skimmeltider går tingene ind i mellem stærkt - vi har ikke adgang til vores gamle kontorer og dermed heller ikke computerudstyr mv. Så vi har gået og ventet på udstyr, og jeg har medbragt mit eget eksterne tastatur og mus i rygsækken hver dag.
Nu ser der så sådan her ud 👀

Wenn Merz der Meinung ist der Bundestag sei kein „Zirkuszelt“, dann soll die Politik bitte auch keinen solchen Zirkus veranstalten.
Wobei wir wohl dazusagen sollten, daß in einem echten Zirkus alles weit geordneter, organisierter und sicherer abläuft.

Dni bez przypadkowego projektu na #setuptools migrującego na `pyproject.toml`, usuwającego plik `MANIFEST.in` i wskutek tego psującego archiwum ze źródłami: [0].

Israeli military used 500lb bomb in strike on Gaza cafe, fragments reveal | Israel-Gaza war | The Guardian https://www.theguardian.com/world/2025/jul/02/israeli-military-bomb-fragments-gaza-al-baqa-cafe

Å reise med tog kan være en prŸvelse.
Bane Nor bŸr ta seg et brett med boller og begynne med ansvarliggjŸring.
Vy også. Standarden på vognsett fra 90 tallet er begredelig. Vedlikehold og renhold likeså.
Er det ikke vognsett med problemer, så er det sporveksler og lyssignaler.
Etter å ha stått stille sŸr for Drammen i tre kvarter, er det bevegelse igjen... men hvor lenge?
#NorskTut

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Elkka:
🎵 Gentle Gaze
#Elkka
https://elkka.bandcamp.com/album/automatic-gentle-gaze
https://open.spotify.com/track/5NVBl4lY3IBWWfrfANxwdI

@… @… https://

#Bisexual people are welcome on my page! 🏳️‍🌈

Die Olympia-Märchen gehen schon wieder los 😂
https://www.mopo.de/hamburg/fuer-olympia-hamburg-plant-gigantische-hyperloop-strecke/

Für Olympia! Hamburg plant gigantische Hyperloop-Strecke (M+)
Noch klingt es mehr nach Science-Fiction als nach einem tatsächlichen Szenario: Hamburg plant an einer Teststrecke für Hyperloop-Technologie. Dabei

Video | Sfeerverslag vanuit zomers Groningen: een stad om heel verliefd op te worden - Sikkom
https://sikkom.nl/nieuws/Video-Hot-town-summer-in-the-city-sfeerverslag-vanuit-zomers-Groningen-46479675.html

@… @… @… It’s hard to believe those trains belong to PKP. It doesn’t feel like that long ago in my childhood (la…

Und wieder breitet
sich im ganzen Haus
der Brotbackduft aus
#Sauerteig

April was a bit of a mess (mentally). But I still had time to play Blue Prince and watch at Oni: Thunder God’s Tale (one of the good things buried in Netflix's catalog).
https://www.davideaversa.it/blog/changelog-april-2025/

The Changelog – April 2025
This month has been harsh. I spent most of it in my head, unable to control a wave of anxiety and catastrophic thoughts. Yet, I tried my best. I read Nexus, watched Conclave just in time for the real one and found another obsucre gem in Netflix back catalog.

🇺🇦 #NowPlaying on BBCRadio3's #NightTracks
Le Motel:
🎵 ChŠm Islands (feat. HoŠng Tuấn)
#LeMotel
https://open.spotify.com/track/25dJjKkzhdcg4OFIpJNlxg

Assabet River

SPACE: Your Genomic Profile Predictor is a Powerful DNA Foundation Model
Zhao Yang, Jiwei Zhu, Bing Su
https://arxiv.org/abs/2506.01833 https://

SPACE: Your Genomic Profile Predictor is a Powerful DNA Foundation Model
Inspired by the success of unsupervised pre-training paradigms, researchers have applied these approaches to DNA pre-training. However, we argue that these approaches alone yield suboptimal results because pure DNA sequences lack sufficient information, since their functions are regulated by genomic profiles like chromatin accessibility. Here, we demonstrate that supervised training for genomic profile prediction serves as a more effective alternative to pure sequence pre-training. Furthermore,…

Starter words did most of it. #Wordle
Wordle 1,473 4/6
⬛🟩⬛⬛🟨
⬛⬛⬛⬛🟨
⬛⬛🟩⬛⬛
🟩🟩🟩🟩🟩

Predicting Empirical AI Research Outcomes with Language Models
Jiaxin Wen, Chenglei Si, Yueh-han Chen, He He, Shi Feng
https://arxiv.org/abs/2506.00794 htt…

Predicting Empirical AI Research Outcomes with Language Models
Many promising-looking ideas in AI research fail to deliver, but their validation takes substantial human labor and compute. Predicting an idea's chance of success is thus crucial for accelerating empirical AI research, a skill that even expert researchers can only acquire through substantial experience. We build the first benchmark for this task and compare LMs with human experts. Concretely, given two research ideas (e.g., two jailbreaking methods), we aim to predict which will perform better…

Lions center Frank Ragnow announces retirement from NFL https://www.nytimes.com/athletic/6397880/2025/06/02/frank-ragnow-nfl-lions-retirement/

[2025-06-03 Tue (UTC), 11 new articles found for math.DG Differential Geometry]
#toXiv_bot_toot

Let's just save money and cancel our fireworks this year. It's going to be fogged over.

Freibad genutzt, Bürgerpflicht erfüllt. Gemeinschaftseinrichtungen nutzen, damit die Vermögenssteuerverweigerer nicht auf die Idee kommen, auch diese gefahrlos einstampfen zu können.
#schwimmen

[2025-06-03 Tue (UTC), 10 new articles found for cs.DS Data Structures and Algorithms]
#toXiv_bot_toot

[2025-06-03 Tue (UTC), 24 new articles found for stat.ME Methodology]
#toXiv_bot_toot

Sitze in der Hitze des Schulhofs, weil gleich irgendeine Stufensitzung mit Eltern starten soll und hier kickt einer Fußball und rennt hinterher.
Was ist denn bloß mit der Jugend los?

Chapeau! Einbürgerungen in der #Schweiz
Artikel von Lukas Tobler (Text) und Florian Bachmann (Foto)
https://www.woz.ch/2522/einbuergerungen/di

Einbürgerungen: «Dieser Fall war perfekt»
Er ist 29, hat noch nicht einmal das Anwaltspatent, und sein Erfolg vor dem Bundesgericht wird die Einbürgerungspraxis in der Schweiz verändern. Eine Begegnung mit Elias Studer.

Projective and anomalous representations of categories and their linearizations
Domenico Fiorenza, Chetan Vuppulury
https://arxiv.org/abs/2506.01521 https:…

Projective and anomalous representations of categories and their linearizations
We invesigate the relation between projective and anomalous representations of categories, and show how to any anomaly $J\colon \mathcal{C}\to 2\mathrm{Vect}$ one can associate an extension $\mathcal{C}^J$ of $\mathcal{C}$ and a subcategory $\mathcal{C}^J_{\mathrm{ST}}$ of $\mathcal{C}^J$ with the property that: (i) anomalous representations of $\mathcal{C}$ with anomaly $J$ are equivalent to $\mathrm{Vect}$-linear functors $E\colon \mathcal{C}^J\to \mathrm{Vect}$, and (ii) these are in turn eq…

[2025-06-03 Tue (UTC), 29 new articles found for cs.CY Computers and Society]
#toXiv_bot_toot

Querying Attack-Fault-Defense Trees: Property Specification in Smart Grid and Aerospace Case Studies
Reza Soltani, Stefano M. Nicoletti, Milan Lopuha\"a-Zwakenberg, Mari\"elle Stoelinga
https://arxiv.org/abs/2506.23789

Querying Attack-Fault-Defense Trees: Property Specification in Smart Grid and Aerospace Case Studies
This paper introduces AFDL, a logic-based framework for reasoning about safety, security, and defense interactions in Attack-Fault-Defense Trees, which is a model that captures all safety, security, and defense domains in a single framework. We showcase both AFDL and propose a structured domain specific query language, LangAFDL, which enables domain experts to express complex analysis goals through intuitive templates. LangAFDL supports both Boolean and quantified queries as well as minimal cut…

Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
Lu\'is Cruz, Jo\~ao Paulo Fernandes, Maja H. Kirkeby, Silverio Mart\'inez-Fern\'andez, June Sallou, Hina Anwar, Enrique Barba Roque, Justus Bogner, Joel Casta\~no, Fernando Castor, Aadil Chasmawala, Sim\~ao Cunha, Daniel Feitosa, Alexandra Gonz\'alez, Andreas Jedlitschka, Patricia Lago, Ana Oprescu, Pooja Rani, Jo\~ao Saraiva, Federica Sarro, Raghavendra…

Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
The environmental impact of Artificial Intelligence (AI)-enabled systems is increasing rapidly, and software engineering plays a critical role in developing sustainable solutions. The "Greening AI with Software Engineering" CECAM-Lorentz workshop (no. 1358, 2025) funded by the Centre Européen de Calcul Atomique et Moléculaire and the Lorentz Center, provided an interdisciplinary forum for 29 participants, from practitioners to academics, to share knowledge, ideas, practices, and current resul…

@… thank you for the share2fedi tool!

One lawsuit just helped melt the fossil fuel industry's defense against being held accountable for climate change
https://phys.org/news/2025-06-lawsuit-fossil-fuel-industry-defense.html

Don’t expect to read independent reporting about ICE activity
— at least not if government officials get their way.
Journalists and members of the public who report on ICE are increasingly under attack by officials who would prefer to silence them so government propaganda can fill the information void.

ICE wants to work in secret. We shouldn’t let it
Journalism about ICE is increasingly under attack by officials who prefer government propaganda

Found a case of party poppers and cap gun caps in the storage room from previous years' pranks.
Order of mousetraps, monofilament line, and metal stakes for securing tripwires should be here by the evening.
Let's see how these raccoons like what I have in store for them...

jokes when they needed my honesty and honesty when they needed my jokes

Gut, dass ein Gericht das festgestellt hat. Mir macht das aber trotzdem große Sorgen. Die CDU kann sich doch nur weiter radikalisieren, sie ist gefangen auf dem Weg immer radikaler werden zu müssen, weil sie glauben nur so die AfD klein halten zu können.
Wo soll das enden? Wie Trump einfach immer mehr Gesetze und Gerichte ignorieren?

Zurückweisung rechtswidrig: Gericht stoppt Asylkurs der Bundesregierung
Das Berliner Verwaltungsgericht erklärt die Zurückweisungen von Asylsuchenden bei Grenzkontrollen für rechtswidrig. Das stellt die Maßnahmen der neuen Bundesregierung infrage.

Donald Trump: The Instagram account proving he’s not actually succeeding at much.
https://slate.com/life/2025/06/donald-trump-news-instagram-account-amanda-mild-takes.html

An mRNA-based seasonal flu vaccine from Moderna was 27 percent more effective at preventing influenza infections than a standard flu shot, the company announced this week.
Moderna noted that the new shot, dubbed "mRNA-1010", hit the highest efficacy target that it set for the trial,
which included nearly 41,000 people aged 50 and above.
Participants were randomly assigned to receive either mRNA-1010 or a standard shot and were then followed for about six months du…

Moderna says mRNA flu vaccine sailed through trial, beating standard shot
Moderna hailed the results, but the shot’s future under RFK Jr. is murky.

Whispers of Many Shores: Cultural Alignment through Collaborative Cultural Expertise
Shuai Feng, Wei-Chuang Chan, Srishti Chouhan, Junior Francisco Garcia Ayala, Srujananjali Medicherla, Kyle Clark, Mingwei Shi
https://arxiv.org/abs/2506.00242

Whispers of Many Shores: Cultural Alignment through Collaborative Cultural Expertise
The integration of large language models (LLMs) into global applications necessitates effective cultural alignment for meaningful and culturally-sensitive interactions. Current LLMs often lack the nuanced understanding required for diverse cultural contexts, and adapting them typically involves costly full fine-tuning. To address this, we introduce a novel soft prompt fine-tuning framework that enables efficient and modular cultural alignment. Our method utilizes vectorized prompt tuning to dyn…

A novel stratified sampler with unbalanced refinement for network reliability assessment
Jianpeng Chan, Iason Papaioannou, Daniel Straub
https://arxiv.org/abs/2506.01044

A novel stratified sampler with unbalanced refinement for network reliability assessment
We investigate stratified sampling in the context of network reliability assessment. We propose an unbalanced stratum refinement procedure, which operates on a partition of network components into clusters and the number of failed components within each cluster. The size of each refined stratum and the associated conditional failure probability, collectively termed failure signatures, can be calculated and estimated using the conditional Bernoulli model. The estimator is further improved by det…

CRScore : Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review
Manav Nitin Kapadnis, Atharva Naik, Carolyn Rose
https://arxiv.org/abs/2506.00296

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review
Reinforcement learning (RL) to improve code review comment generation requires handling unstructured outputs, making reinforcement learning (RL) feedback challenging. The two main RL approaches, namely RL with Verifiable Feedback (RLVR) and RL with AI Feedback (RLAIF), offer trade-offs: RLVR provides reliable feedback for structured tasks like code generation, while RLAIF works for unstructured outputs but is subjective. We bridge this gap with CRScore++, an RL framework that leverages both LLM…

Lions' Frank Ragnow retires: All-Pro center ends career after seven seasons in Detroit, citing health concerns

https://www.cbssports.com/n…

A 0.51-Approximation of Maximum Matching in Sublinear $n^{1.5}$ Time
Sepideh Mahabadi, Mohammad Roghani, Jakub Tarnawski
https://arxiv.org/abs/2506.01669 h…

A 0.51-Approximation of Maximum Matching in Sublinear $n^{1.5}$ Time
We study the problem of estimating the size of a maximum matching in sublinear time. The problem has been studied extensively in the literature and various algorithms and lower bounds are known for it. Our result is a $0.5109$-approximation algorithm with a running time of $\tilde{O}(n\sqrt{n})$. All previous algorithms either provide only a marginal improvement (e.g., $2^{-280}$) over the $0.5$-approximation that arises from estimating a \emph{maximal} matching, or have a running time that i…

Building nonstationary extreme value model using L-moments
Yire Shin, Yonggwan Shin, Jeong-Soo Park
https://arxiv.org/abs/2506.00977 https://

Building nonstationary extreme value model using L-moments
The maximum likelihood estimation for a time-dependent nonstationary (NS) extreme value model is often too sensitive to influential observations, such as large values toward the end of a sample. Thus, alternative methods using L-moments have been developed in NS models to address this problem while retaining the advantages of the stationary L-moment method. However, one method using L-moments displays inferior performance compared to stationary estimation when the data exhibit a positive trend …

Behavioral Augmentation of UML Class Diagrams: An Empirical Study of Large Language Models for Method Generation
Djaber Rouabhia, Ismail Hadjadj
https://arxiv.org/abs/2506.00788

The Price of Being Partial: Complexity of Partial Generalized Dominating Set on Bounded-Treewidth Graphs
Jakob Greilhuber, D\'aniel Marx
https://arxiv.org/abs/2506.01645

The Price of Being Partial: Complexity of Partial Generalized Dominating Set on Bounded-Treewidth Graphs
The $(σ, ρ)$-domination framework introduced by Telle [Nord. J. Comput.'94] captures many classical graph problems. For fixed sets $σ, ρ$ of non-negative integers, a $(σ,ρ)$-set of a graph $G$ is a set $S$ such that for every $v\in V(G)$, we have (1) if $v \in S$, then $|N(v) \cap S| \in σ$, and (2) if $v \not\in S$, then $|N(v) \cap S| \in ρ$. We initiate the study of a natural partial variant of the problem, in which the constraints given by $σ, ρ$ need not be fu…

Improved Risk Ratio Approximation by Complementary Log-Log Models: A Comparison with Logistic Models
Yuji Tsubota, Kenji Beppu
https://arxiv.org/abs/2506.00889

Improved Risk Ratio Approximation by Complementary Log-Log Models: A Comparison with Logistic Models
Odds ratios obtained from logistic models fail to approximate risk ratios with common outcomes, leading to potential misinterpretations about exposure effects by practitioners. This article investigates the complementary log-log models as a practical alternative to produce risk ratio approximation. We demonstrate that the corresponding effect measure of complementary log-log models, called the complementary log ratio in this article, consistently provides a closer approximation to risk ratios t…

A Ranking Framework for Network Resource Allocation and Scheduling via Hypergraphs
Rajpreet Singh, Novak Bo\v{s}kov, Aditya Gudal, Manzoor A. Khan
https://arxiv.org/abs/2506.01571

A Ranking Framework for Network Resource Allocation and Scheduling via Hypergraphs
Resource allocation and scheduling are a common problem in various distributed systems. Although widely studied, the state-of-the-art solutions either do not scale or lack the expressive power to capture the most complex instances of the problem. To that end, we present a mathematical framework for hypergraph ranking and analysis, unifying graph theory, lattice theory, and semantic analysis. In our fundamental theorem, we prove the existence of partial order on entities of hypergraphs, extendin…

Recover Experimental Data with Selection Bias using Counterfactual Logic
Jingyang He, Shuai Wang, Ang Li
https://arxiv.org/abs/2506.00335 https://

Recover Experimental Data with Selection Bias using Counterfactual Logic
Selection bias, arising from the systematic inclusion or exclusion of certain samples, poses a significant challenge to the validity of causal inference. While Bareinboim et al. introduced methods for recovering unbiased observational and interventional distributions from biased data using partial external information, the complexity of the backdoor adjustment and the method's strong reliance on observational data limit its applicability in many practical settings. In this paper, we formally di…

Reweighted Spectral Partitioning Works: Bounds for Special Graph Classes
Jack Spalding-Jamieson
https://arxiv.org/abs/2506.01228 https://

Reweighted Spectral Partitioning Works: Bounds for Special Graph Classes
Spectral partitioning is a method that can be used to compute small sparse cuts or small edge-separators in a wide variety of graph classes, by computing the second-smallest eigenvalue (and eigenvector) of the Laplacian matrix. Upper bounds on this eigenvalue for certain graph classes imply that the method obtains small edge-separators for these classes, usually with a sub-optimal dependence on the maximum degree. In this work, we show that a related method, called reweighted spectral partition…

Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
Maryam Aliakbarpour, Zhan Shi, Ria Stevens, Vincent X. Wang
https://arxiv.org/abs/2506.01162 …

Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
Estimating the density of a distribution from its samples is a fundamental problem in statistics. Hypothesis selection addresses the setting where, in addition to a sample set, we are given $n$ candidate distributions -- referred to as hypotheses -- and the goal is to determine which one best describes the underlying data distribution. This problem is known to be solvable very efficiently, requiring roughly $O(\log n)$ samples and running in $\tilde{O}(n)$ time. The quality of the output is mea…

Tree-based methods for estimating heterogeneous model performance and model combining
Ruotao Zhang, Constantine Gatsonis, Jon Steingrimsson
https://arxiv.org/abs/2506.01905

Tree-based methods for estimating heterogeneous model performance and model combining
Model performance is frequently reported only for the overall population under consideration. However, due to heterogeneity, overall performance measures often do not accurately represent model performance within specific subgroups. We develop tree-based methods for the data-driven identification of subgroups with differential model performance, where splitting decisions are made to maximize heterogeneity in performance between subgroups. We extend these methods to tree ensembles, including bot…

BWT for string collections
Davide Cenzato, Zsuzsanna Lipt\'ak, Nadia Pisanti, Giovanna Rosone, Marinella Sciortino
https://arxiv.org/abs/2506.01092 htt…

BWT for string collections
We survey the different methods used for extending the BWT to collections of strings, following largely [Cenzato and Lipták, CPM 2022, Bioinformatics 2024]. We analyze the specific aspects and combinatorial properties of the resulting BWT variants and give a categorization of publicly available tools for computing the BWT of string collections. We show how the specific method used impacts on the resulting transform, including the number of runs, and on the dynamicity of the transform with resp…

An Efficient and Interpretable Autoregressive Model for High-Dimensional Tensor-Valued Time Series
Yuxi Cai, Lan Li, Yize Wang, Guodong Li
https://arxiv.org/abs/2506.01658

An Efficient and Interpretable Autoregressive Model for High-Dimensional Tensor-Valued Time Series
In autoregressive modeling for tensor-valued time series, Tucker decomposition, when applied to the coefficient tensor, provides a clear interpretation of supervised factor modeling but loses its efficiency rapidly with increasing tensor order. Conversely, canonical polyadic (CP) decomposition maintains efficiency but lacks a precise statistical interpretation. To attain both interpretability and powerful dimension reduction, this paper proposes a novel approach under the supervised factor mode…

Learning DNF through Generalized Fourier Representations
Mohsen Heidari, Roni Khardon
https://arxiv.org/abs/2506.01075 https://arxiv.…

Learning DNF through Generalized Fourier Representations
The Fourier representation for the uniform distribution over the Boolean cube has found numerous applications in algorithms and complexity analysis. Notably, in learning theory, learnability of Disjunctive Normal Form (DNF) under uniform as well as product distributions has been established through such representations. This paper makes five main contributions. First, it introduces a generalized Fourier expansion that can be used with any distribution $D$ through the representation of the distr…

A nonparametric statistical method for deconvolving densities in the analysis of proteomic data
Akin Anarat, Jean Krutmann, Holger Schwender
https://arxiv.org/abs/2506.01540

A nonparametric statistical method for deconvolving densities in the analysis of proteomic data
In medical research, often, genomic or proteomic data are collected, with measurements frequently subject to uncertainties or errors, making it crucial to accurately separate the signals of the genes or proteins, respectively, from the noise. Such a signal separation is also of interest in skin aging research in which intrinsic aging driven by genetic factors and extrinsic, i.e.\ environmentally induced, aging are investigated by considering, e.g., the proteome of skin fibroblasts. Since extrin…

Controlling the Spread of Epidemics on Networks with Differential Privacy
Dung Nguyen, Aravind Srinivasan, Renata Valieva, Anil Vullikanti, Jiayi Wu
https://arxiv.org/abs/2506.00745

Controlling the Spread of Epidemics on Networks with Differential Privacy
Designing effective strategies for controlling epidemic spread by vaccination is an important question in epidemiology, especially in the early stages when vaccines are limited. This is a challenging question when the contact network is very heterogeneous, and strategies based on controlling network properties, such as the degree and spectral radius, have been shown to be effective. Implementation of such strategies requires detailed information on the contact structure, which might be sensitiv…

Simulating Complex Crossectional and Longitudinal Data using the simDAG R Package
Robin Denz, Nina Timmesfeld
https://arxiv.org/abs/2506.01498 https://

Simulating Complex Crossectional and Longitudinal Data using the simDAG R Package
Generating artificial data is a crucial step when performing Monte-Carlo simulation studies. Depending on the planned study, complex data generation processes (DGP) containing multiple, possibly time-varying, variables with various forms of dependencies and data types may be required. Simulating data from such DGP may therefore become a difficult and time-consuming endeavor. The simDAG R package offers a standardized approach to generate data from simple and complex DGP based on the definition …

Faster negative length shortest paths by bootstrapping hop reducers
Yufan Huang, Peter Jin, Kent Quanrud
https://arxiv.org/abs/2506.00428 https://

Faster negative length shortest paths by bootstrapping hop reducers
The textbook algorithm for real-weighted single-source shortest paths takes $O(m n)$ time on a graph with $m$ edges and $n$ vertices. The breakthrough algorithm by Fineman [Fin24] takes $\tilde{O}(m n^{8/9})$ randomized time. The running time was subsequently improved to $\tilde{O}(mn^{4/5})$ [HJQ25]. We build on [Fin24; HJQ25] to obtain an $\tilde{O}(m n^{3/4} + m^{4/5} n)$ randomized running time. (Equivalently, $\tilde{O}(mn^{3/4})$ for $m \geq n^{5/4}$, and $\tilde{O}(m^{4/5} n)$ for $m \…

Characterization based Goodness-of-Fit for Generalized Pareto Distribution: A Blend of Stein's Identity and Dynamic Survival Extropy
Gaurav Kandpal, Nitin Gupta
https://arxiv.org/abs/2506.01473

Characterization based Goodness-of-Fit for Generalized Pareto Distribution: A Blend of Stein's Identity and Dynamic Survival Extropy
This paper proposes a goodness of fit test for the generalized Pareto distribution (GPD). Firstly, we provide two characterizations of GPD based on Stein's identity and dynamic survival extropy. These characterizations are used to test GPD separately for the positive and negative shape parameter cases. A Monte Carlo simulation is conducted to provide the critical values and power of the proposed test against a good number of alternatives. Our test is simple to use and it has asymptotic normalit…

Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten
https://arxiv.org/abs/2506.00165

Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Randomized dimensionality reduction is a widely-used algorithmic technique for speeding up large-scale Euclidean optimization problems. In this paper, we study dimension reduction for a variety of maximization problems, including max-matching, max-spanning tree, max TSP, as well as various measures for dataset diversity. For these problems, we show that the effect of dimension reduction is intimately tied to the \emph{doubling dimension} $λ_X$ of the underlying dataset $X$ -- a quantity measur…

e-GAI: e-value-based Generalized $\alpha$-Investing for Online False Discovery Rate Control
Yifan Zhang, Zijian Wei, Haojie Ren, Changliang Zou
https://arxiv.org/abs/2506.01452

e-GAI: e-value-based Generalized $α$-Investing for Online False Discovery Rate Control
Online multiple hypothesis testing has attracted a lot of attention in many applications, e.g., anomaly status detection and stock market price monitoring. The state-of-the-art generalized $α$-investing (GAI) algorithms can control online false discovery rate (FDR) on p-values only under specific dependence structures, a situation that rarely occurs in practice. The e-LOND algorithm (Xu & Ramdas, 2024) utilizes e-values to achieve online FDR control under arbitrary dependence but suffers from …

High-Dimensional Regularized Additive Matrix Autoregressive Model
Debika Ghosh, Samrat Roy, Nilanjana Chakraborty
https://arxiv.org/abs/2506.01403 https://…

High-Dimensional Regularized Additive Matrix Autoregressive Model
High-dimensional time series has diverse applications in econometrics and finance. Recent models for capturing temporal dependence have employed a bilinear representation for matrix time series, or the Tucker-decomposition based representation in case of tensor time series. A bilinear or Tucker-decomposition based temporal effect is difficult to interpret on many occasions, along with its computational complexity due to the non-convex nature of the underlying optimization problem. Moreover, the…

Neural Networks for Parameter Estimation of the Discretely Observed Hawkes Process
Jason J. Lambe, Feng Chen, Tom Stindl, Tsz-Kit Jeffrey Kwan
https://arxiv.org/abs/2506.01258

Neural Networks for Parameter Estimation of the Discretely Observed Hawkes Process
When the sample path of a Hawkes process is observed discretely, such that only the total event counts in disjoint time intervals are known, the likelihood function becomes intractable. To overcome the challenge of likelihood-based inference in this setting, we propose to use a likelihood-free approach to parameter estimation, where a fully connected neural network (NN) is trained using simulated data to estimate the parameters of the Hawkes process from a summary statistic of the count data. A…

Reluctant Interaction Inference after Additive Modeling
Yiling Huang, Snigdha Panigrahi, Guo Yu, Jacob Bien
https://arxiv.org/abs/2506.01219 https://

Reluctant Interaction Inference after Additive Modeling
Additive models enjoy the flexibility of nonlinear models while still being readily understandable to humans. By contrast, other nonlinear models, which involve interactions between features, are not only harder to fit but also substantially more complicated to explain. Guided by the principle of parsimony, a data analyst therefore may naturally be reluctant to move beyond an additive model unless it is truly warranted. To put this principle of interaction reluctance into practice, we formula…

Uncovering Bias Mechanisms in Observational Studies
Ilker Demirel, Zeshan Hussain, Piersilvio De Bartolomeis, David Sontag
https://arxiv.org/abs/2506.01191

Uncovering Bias Mechanisms in Observational Studies
Observational studies are a key resource for causal inference but are often affected by systematic biases. Prior work has focused mainly on detecting these biases, via sensitivity analyses and comparisons with randomized controlled trials, or mitigating them through debiasing techniques. However, there remains a lack of methodology for uncovering the underlying mechanisms driving these biases, e.g., whether due to hidden confounding or selection of participants. In this work, we show that the r…

Flexible Selective Inference with Flow-based Transport Maps
Sifan Liu, Snigdha Panigrahi
https://arxiv.org/abs/2506.01150 https://arx…

Flexible Selective Inference with Flow-based Transport Maps
Data-carving methods perform selective inference by conditioning the distribution of data on the observed selection event. However, existing data-carving approaches typically require an analytically tractable characterization of the selection event. This paper introduces a new method that leverages tools from flow-based generative modeling to approximate a potentially complex conditional distribution, even when the underlying selection event lacks an analytical description -- take, for example,…

ProjMC$^2$: Scalable and Stable Posterior Inference for Bayesian Spatial Factor Models with Application to Spatial Transcriptomics
Lu Zhang
https://arxiv.org/abs/2506.01098

ProjMC$^2$: Scalable and Stable Posterior Inference for Bayesian Spatial Factor Models with Application to Spatial Transcriptomics
Factor models exhibit a fundamental tradeoff among flexibility, identifiability, and computational efficiency. Bayesian spatial factor models, in particular, face pronounced identifiability concerns and scaling difficulties. To mitigate these issues and enhance posterior inference reliability, this work proposes Projected Markov Chain Monte Carlo (ProjMC$^2$), a novel Markov Chain Monte Carlo (MCMC) sampling algorithm employing projection techniques and conditional conjugacy. ProjMC$^2$ is show…

Factorized Tail Volatility Model: Augmenting Excess-over-Threshold Method for High-Dimensional Hevay-Tailed Data
Yifan Hu, Yanxi Hou
https://arxiv.org/abs/2506.00840

Factorized Tail Volatility Model: Augmenting Excess-over-Threshold Method for High-Dimensional Hevay-Tailed Data
Ecess-over-Threshold method is a crucial technique in extreme value analysis, which approximately models larger observations over a threshold using a Generalized Pareto Distribution. This paper presents a comprehensive framework for analyzing tail risk in high-dimensional data by introducing the Factorized Tail Volatility Model (FTVM) and integrating it with central quantile models through the EoT method. This integrated framework is termed the FTVM-EoT method. In this framework, a quantile-rel…

Uncertainty quantification of synchrosqueezing transform under complicated nonstationary noise
Hau-Tieng Wu, Zhou Zhou
https://arxiv.org/abs/2506.00779 htt…

Uncertainty quantification of synchrosqueezing transform under complicated nonstationary noise
We propose a bootstrapping algorithm to quantify the uncertainty of the time-frequency representation (TFR) generated by the short-time Fourier transform (STFT)-based synchrosqueezing transform (SST) when the input signal is oscillatory with time-varying amplitude and frequency and contaminated by complex nonstationary noise. To this end, we leverage a recently developed high-dimensional Gaussian approximation technique to establish a sequential Gaussian approximation for nonstationary random p…

Unbiased estimation in new Gini index extensions under gamma distributions
Roberto Vila, Helton Saulo
https://arxiv.org/abs/2506.00666 https://

Unbiased estimation in new Gini index extensions under gamma distributions
In this paper, we propose two new flexible Gini indices (extended lower and upper) defined via differences between the $i$-th observation, the smallest order statistic, and the largest order statistic, for any $1 \leqslant i \leqslant m$. For gamma-distributed data, we obtain exact expectations of the estimators and establish their unbiasedness, generalizing prior works by [Deltas, G. 2003. The small-sample bias of the gini coefficient: Results and implications for empirical research. Review of…

Estimands for Randomized Discontinuation Designs in Oncology
Ayon Mukherjee, Oleksandr Sverdlov, Ngoc-Thuy Ha, Yu Deng
https://arxiv.org/abs/2506.00556 htt…

Estimands for Randomized Discontinuation Designs in Oncology
Randomized discontinuation design (RDD) is an enrichment strategy commonly used to address limitations of traditional placebo-controlled trials, particularly the ethical concern of prolonged placebo exposure. RDD consists of two phases: an initial open-label phase in which all eligible patients receive the investigational medicinal product (IMP), followed by a double-blind phase in which responders are randomized to continue with the IMP or switch to placebo. This design tests whether the IMP p…

Estimation of Optimal Causal Bounds via Covariate-Assisted Optimal Transport
Sirui Lin, Zijun Gao, Jose Blanchet, Peter Glynn
https://arxiv.org/abs/2506.00257

Estimation of Optimal Causal Bounds via Covariate-Assisted Optimal Transport
We study the estimation of causal estimand involving the joint distribution of treatment and control outcomes for a single unit. In typical causal inference settings, it is impossible to observe both outcomes simultaneously, which places our estimation within the domain of partial identification (PI). Pre-treatment covariates can substantially reduce estimation uncertainty by shrinking the partially identified set. Recently, it was shown that covariate-assisted PI sets can be characterized thro…

Integrating Expert Knowledge and Recursive Bayesian Inference: A Framework for Spatial and Spatio-Temporal Data Challenges
Mario Figueira, David Conesa, Antonio L\'opez-Qu\'ilez, H{\aa}vard Rue
https://arxiv.org/abs/2506.00221

Integrating Expert Knowledge and Recursive Bayesian Inference: A Framework for Spatial and Spatio-Temporal Data Challenges
Expert elicitation is a critical approach for addressing data scarcity across various disciplines. But moreover, it can also complement big data analytics by mitigating the limitations of observational data, such as incompleteness and reliability issues, thereby enhancing model estimates through the integration of disparate or conflicting data sources. The paper also outlines various strategies for integrating prior information within the Integrated Nested Laplace Approximation method and propo…