arXiv:2510.02513v2 Announce Type: replace-cross
Abstract: Adaptive randomized pivoting (ARP) is a recently proposed and highly effective algorithm for column subset selection. This paper reinterprets the ARP algorithm by drawing connections to the vol…
arXiv:2604.02555v1 Announce Type: cross
Abstract: We construct algorithms with optimal error for learning with adversarial noise. The overarching theme of this work is that the use of \textsl{randomized} hypotheses can substantially improve upon the b…
arXiv:2507.18021v2 Announce Type: replace-cross
Abstract: We study the zeroth-order query complexity of sampling from a general logconcave distribution: given access to an evaluation oracle for a convex function $V:\mathbb{R}^{d}\rightarrow\mathbb{R}\…
arXiv:2510.16609v2 Announce Type: replace
Abstract: Test-time augmentation, such as Retrieval-Augmented Generation (RAG) or tool use, critically depends on an interplay between a model’s parametric knowledge and externally retrieved information. Howev…
arXiv:2511.02272v3 Announce Type: replace-cross
Abstract: Probabilistic relaxations of graph cuts offer a differentiable alternative to spectral clustering, enabling end-to-end and online learning without eigendecompositions, yet prior work centered o…
arXiv:2604.00963v1 Announce Type: cross
Abstract: We show polylogarithmic mixing time bounds for the alternating-scan sampler for positively weighted restricted Boltzmann machines. This is done via analysing the same chain and the Glauber dynamics for…
arXiv:2512.15987v2 Announce Type: replace
Abstract: It is widely believed that complex machine learning models generally encode features through linear representations. This is the foundational hypothesis behind a vast body of work on interpretability…
arXiv:2508.12627v2 Announce Type: replace
Abstract: Higher-order $U$-statistics abound in fields such as statistics, machine learning, and computer science, but are known to be highly time-consuming to compute in practice. Despite their widespread app…
arXiv:2603.27154v1 Announce Type: new
Abstract: Entity resolution — identifying database records that refer to the same real-world entity — is naturally modelled on bipartite graphs connecting entity nodes to their attribute values. Applying a messa…
arXiv:2603.27462v1 Announce Type: cross
Abstract: Matrix-vector multiplication is a fundamental building block in neural networks, vector databases, and large language models, particularly during inference. As a result, efficient matrix-vector multipl…