Tootfinder

Great thread over on Bluesky by one of the (the) main dev for the app, commenting on #JackDorsey comments about why he left BlueSky (company and network)
Remember folks, it ain’t Mastodon v BlueSky (IMO)
https://

This https://arxiv.org/abs/2011.10019 has been replaced.
link: https://scholar.google.com/scholar?q=a

Weakly holonomic for equivariant $\mathcal{D}$-modules on rigid analytic spaces
Let G be a $p$-adic Lie group. We develop a dimension theory for coadmissible G-equivariant $\mathcal{D}$-modules on smooth rigid analytic spaces. We introduce the category of weakly holonomic G-equivariant $\mathcal{D}$-modules, study its duality and its preservation under various operations.

New Harms Moderated by Immersive Experiences and Breaks in Them
Eugene Kukshinov
https://arxiv.org/abs/2405.05926 https://arxiv.org/p…

New Harms Moderated by Immersive Experiences and Breaks in Them
This proposal highlights the potential real-world consequences of harmful experiences in immersive and embodied spaces due to presence, which moderates experiences, intensifying positive or negative content. While positive experiences enhance social interactions, negative content can lead to harm. Also, presence is not continuous and may break. Understanding the threshold between harmful experiences and breaks in presence is essential. This proposal underscores the need to explore whether the l…

This https://arxiv.org/abs/1807.05477 has been replaced.
link: https://scholar.google.com/scholar?q=a

Linear Programming Based Near-Optimal Pricing for Laminar Bayesian Online Selection
The Bayesian online selection problem aims to design a pricing scheme for a sequence of arriving buyers that maximizes the expected social welfare (or revenue) subject to different structural constraints. Inspired by applications with a hierarchy of service, this paper focuses on the cases where a laminar matroid characterizes the set of served buyers. We give the first Polynomial-Time Approximation Scheme (PTAS) for the problem when the laminar matroid has constant depth. Our approach is based…

An Adaptive Dimension Reduction Estimation Method for High-dimensional Bayesian Optimization
Shouri Hu, Jiawei Li, Zhibo Cai
https://arxiv.org/abs/2403.05425

An Adaptive Dimension Reduction Estimation Method for High-dimensional Bayesian Optimization
Bayesian optimization (BO) has shown impressive results in a variety of applications within low-to-moderate dimensional Euclidean spaces. However, extending BO to high-dimensional settings remains a significant challenge. We address this challenge by proposing a two-step optimization framework. Initially, we identify the effective dimension reduction (EDR) subspace for the objective function using the minimum average variance estimation (MAVE) method. Subsequently, we construct a Gaussian proce…

Modular curves $X_1(n)$ as moduli spaces of point arrangements and applications
Lev Borisov, Xavier Roulleau
https://arxiv.org/abs/2404.04364 https://

Modular curves $X_1(n)$ as moduli spaces of point arrangements and applications
For a complex elliptic curve $E$ and a point $p$ of order $n$ on it, the images of the points $p_k=kp$ under the Weierstrass embedding of $E$ into $\mathbb{C}\mathbb{P}^2$ are collinear if and only if the sum of indices is divisible by $n$. Thus, it provides a realization of a certain matroid. We study this matroid in detail and prove that its realization space is isomorphic (over $\mathbb{C}$) to the modular curve $X_1(n)$, provided $n\geq 10$, which also provides an integral model of $X_1(n)$…

Remarks by President Biden, President Obama, and President Clinton in a Moderated Conversation with Stephen Colbert at a Campaign Reception | New York, NY (The White House)
https://www.whitehouse.gov/briefing-room/speeches-remarks/2024/03/28/remarks-by-president-biden-president-obama-and-president-clinton-in-a-moderated-conversation-with-stephen-colbert-at-a-campaign-reception-new-york-ny/
http://www.memeorandum.com/240329/p60#a240329p60

New Harms Moderated by Immersive Experiences and Breaks in Them
Eugene Kukshinov
https://arxiv.org/abs/2405.05926 https://arxiv.org/p…

New Harms Moderated by Immersive Experiences and Breaks in Them
This proposal highlights the potential real-world consequences of harmful experiences in immersive and embodied spaces due to presence, which moderates experiences, intensifying positive or negative content. While positive experiences enhance social interactions, negative content can lead to harm. Also, presence is not continuous and may break. Understanding the threshold between harmful experiences and breaks in presence is essential. This proposal underscores the need to explore whether the l…

This https://arxiv.org/abs/2108.05733 has been replaced.
link: https://scholar.google.com/scholar?q=a

Relating homomorphism spaces between Specht modules of different degrees
Let $K$ be an infinite field of characteristic $p>0$ and let $λ, μ$ be partitions of $n$, where $λ=(λ_1,...,λ_n)$ and $μ=(μ_1,..,μ_n)$. By $S^λ$ we denote the Specht module corresponding to $λ$ for the group algebra $K\mathfrak{S}_n$ of the symmetric group $\mathfrak{S}_n$. D. Hemmer has raised the question of relating the homomorphism spaces $\Hom_{\mathfrak{S}_n}(S^μ, S^λ)$ and $\Hom_{\mathfrak{S}_{n'}}(S^{μ^+}, S^{λ^+})$, where $n'=n+kp^d$, $λ^+ =λ+(kp^{d})$, $μ^+=μ+(kp^{d}…

Dynamic Human Trust Modeling of Autonomous Agents With Varying Capability and Strategy
Jason Dekarske (University of California, Davis), Zhaodan Kong (University of California, Davis), Sanjay Joshi (University of California, Davis)
https://arxiv.org/abs/2404.19291 https://arxiv.org/pdf/2404.19291
arXiv:2404.19291v1 Announce Type: new
Abstract: Objective We model the dynamic trust of human subjects in a human-autonomy-teaming screen-based task.
Background Trust is an emerging area of study in human-robot collaboration. Many studies have looked at the issue of robot performance as a sole predictor of human trust, but this could underestimate the complexity of the interaction.
Method Subjects were paired with autonomous agents to search an on-screen grid to determine the number of outlier objects. In each trial, a different autonomous agent with a preassigned capability used one of three search strategies and then reported the number of outliers it found as a fraction of its capability. Then, the subject reported their total outlier estimate. Human subjects then evaluated statements about the agent's behavior, reliability, and their trust in the agent.
Results 80 subjects were recruited. Self-reported trust was modeled using Ordinary Least Squares, but the group that interacted with varying capability agents on a short time order produced a better performing ARIMAX model. Models were cross-validated between groups and found a moderate improvement in the next trial trust prediction.
Conclusion A time series modeling approach reveals the effects of temporal ordering of agent performance on estimated trust. Recency bias may affect how subjects weigh the contribution of strategy or capability to trust. Understanding the connections between agent behavior, agent performance, and human trust is crucial to improving human-robot collaborative tasks.
Application The modeling approach in this study demonstrates the need to represent autonomous agent characteristics over time to capture changes in human trust.