Tootfinder

Next stop in our NLP timeline is 2013, the introduction of low dimensional dense word vectors - so-called "word embeddings" - based on distributed semantics, as e.g. word2vec by Mikolov et al. from Google, which enabled representation learning on text.
T. Mikolov et al. (2013). Efficient Estimation of Word Representations in Vector Space.
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Efficient Estimation of Word Representations in Vector Space
We propose two novel model architectures for computing continuous vector representations of words from very large data sets. The quality of these representations is measured in a word similarity task, and the results are compared to the previously best performing techniques based on different types of neural networks. We observe large improvements in accuracy at much lower computational cost, i.e. it takes less than a day to learn high quality word vectors from a 1.6 billion words data set. Fur…

This https://arxiv.org/abs/2506.04668 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Feature-Based Lie Group Transformer for Real-World Applications
The main goal of representation learning is to acquire meaningful representations from real-world sensory inputs without supervision. Representation learning explains some aspects of human development. Various neural network (NN) models have been proposed that acquire empirically good representations. However, the formulation of a good representation has not been established. We recently proposed a method for categorizing changes between a pair of sensory inputs. A unique feature of this approa…

On the spectra of prefix-reversal graphs
Sa\'ul A. Blanco, Charles Buehrle
https://arxiv.org/abs/2506.08345 https://arxiv.org/pdf…

On the spectra of prefix-reversal graphs
In this paper, we study spectral properties of prefix-reversal graphs. These graphs are obtained by connecting two elements of $C_m\wr S_n$ via prefix reversals. If $m=1,2$, the corresponding prefix-reversal graphs are the classic pancake and burnt pancake graphs. If $m>2$, then one can consider the directed and undirected versions of these graphs. We prove that the spectrum of the undirected prefix-reversal graph $\mathbb{P}_m(n)$ contains all even integers in the interval $[0,2n]\setminus\{2\…

This https://arxiv.org/abs/2410.22931 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A Third-Order Gaussian Process Trajectory Representation Framework with Closed-Form Kinematics for Continuous-Time Motion Estimation
In this paper, we propose a third-order, i.e., white-noise-on-jerk, Gaussian Process (GP) Trajectory Representation (TR) framework for continuous-time (CT) motion estimation (ME) tasks. Our framework features a unified trajectory representation that encapsulates the kinematic models of both $SO(3)\times\mathbb{R}^3$ and $SE(3)$ pose representations. This encapsulation strategy allows users to use the same implementation of measurement-based factors for either choice of pose representation, whic…

my annoying engineering trait is that i don't like hardware abstraction layers
they're usually irritating to write code for, and equally irritating to reverse-engineer whenever i need to. i mostly end up reverse-engineering these days

Generating representative macrobenchmark microservice systems from distributed traces with Palette
Vaastav Anand, Matheus Stolet, Jonathan Mace, Antoine Kaufmann
https://arxiv.org/abs/2506.06448

Generating representative macrobenchmark microservice systems from distributed traces with Palette
Microservices are the dominant design for developing cloud systems today. Advancements for microservice need to be evaluated in representative systems, e.g. with matching scale, topology, and execution patterns. Unfortunately in practice, researchers and practitioners alike often do not have access to representative systems. Thus they have to resort to sub-optimal non-representative alternatives, e.g. small and oversimplified synthetic benchmark systems or simulated system models instead. …

flickr_growth: Flickr friendship network (2008)
A network of declared friendships among Frickr users. Nodes represent Frickr users and a directed edge (i,j) represents a directed declaration of friendship from i to j. Edges are timestamped.
This network has 2302925 nodes and 33140017 edges.
Tags: Social, Online, Unweighted, Timestamps
h…

Employing Discrete Fourier Transform in Representational Learning
Raoof HojatJalali, Edmondo Trentin
https://arxiv.org/abs/2506.06765 https://

Employing Discrete Fourier Transform in Representational Learning
Image Representation learning via input reconstruction is a common technique in machine learning for generating representations that can be effectively utilized by arbitrary downstream tasks. A well-established approach is using autoencoders to extract latent representations at the network's compression point. These representations are valuable because they retain essential information necessary for reconstructing the original input from the compressed latent space. In this paper, we propose an…

I realize there's a lot going on, but I'm surprised I didn't hear anything about the Richmond-San Rafael Bridge partially shutting down for emergency repairs. How does this affect the bike path debate? No word if it's affected by the shutdown.
https://www.

This https://arxiv.org/abs/2505.18132 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

BiggerGait: Unlocking Gait Recognition with Layer-wise Representations from Large Vision Models
Large vision models (LVM) based gait recognition has achieved impressive performance. However, existing LVM-based approaches may overemphasize gait priors while neglecting the intrinsic value of LVM itself, particularly the rich, distinct representations across its multi-layers. To adequately unlock LVM's potential, this work investigates the impact of layer-wise representations on downstream recognition tasks. Our analysis reveals that LVM's intermediate layers offer complementary properties a…