Papers
Scaling Capability in Token Space: An Analysis of Large Vision Language Model
Tenghui Li, Guoxu Zhou, Xuyang Zhao et al.
Minimax Optimal Two-Sample Testing under Local Differential Privacy
Jongmin Mun, Seungwoo Kwak, Ilmun Kim
Jackpot: Approximating Uncertainty Domains with Adversarial Manifolds
Nathanaël Munier, Emmanuel Soubies, Pierre Weiss
An Asymptotically Optimal Coordinate Descent Algorithm for Learning Bayesian Networks from Gaussian Models
Tong Xu, Simge Küçükyavuz, Ali Shojaie et al.
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation
David Holzmüller, Francis Bach
A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning
Samuel E. Otto, Nicholas Zolman, J. Nathan Kutz et al.
Infinite-dimensional Mahalanobis Distance with Applications to Kernelized Novelty Detection
Nikita Zozoulenko, Thomas Cass, Lukas Gonon
Stable learning using spiking neural networks equipped with affine encoders and decoders
A. Martina Neuman, Dominik Dold, Philipp Christian Petersen
Efficient Knowledge Deletion from Trained Models Through Layer-wise Partial Machine Unlearning
Vinay Chakravarthi Gogineni, Esmaeil S. Nadimi
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
Kuo-Wei Lai, Vidya Muthukumar
Piecewise deterministic sampling with splitting schemes
Andrea Bertazzi, Paul Dobson, Pierre Monmarché
Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2
Yuri Chervonyi, Trieu H. Trinh, Miroslav Olšák et al.
Decentralized Bilevel Optimization: A Perspective from Transient Iteration Complexity
Boao Kong, Shuchen Zhu, Songtao Lu et al.
Fair Text Classification via Transferable Representations
Thibaud Leteno, Michael Perrot, Charlotte Laclau et al.
Stochastic Interior-Point Methods for Smooth Conic Optimization with Applications
Chuan He, Zhanwang Deng
Generalized multi-view model: Adaptive density estimation under low-rank constraints
Julien Chhor, Olga Klopp, Alexandre B. Tsybakov
(De)-regularized Maximum Mean Discrepancy Gradient Flow
Zonghao Chen, Aratrika Mustafi, Pierre Glaser et al.
On Probabilistic Embeddings in Optimal Dimension Reduction
Ryan Murray, Adam Pickarski
Physics Informed Kolmogorov-Arnold Neural Networks for Dynamical Analysis via Efficient-KAN and WAV-KAN
Subhajit Patra, Sonali Panda, Bikram Keshari Parida et al.
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples
Leo L. Duan, Anirban Bhattacharya
Online Quantile Regression
Yinan Shen, Dong Xia, Wen-Xin Zhou
Statistical Inference of Random Graphs With a Surrogate Likelihood Function
Dingbo Wu, Fangzheng Xie