Papers
When and How Often is Weighted Majority Vote Optimal Under Log Loss?
Steven An, Sanjoy Dasgupta
Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization
Theophilus Amaefuna, Hitesh Ulhas Vaidya, Anshuman Chhabra et al.
PCU: Perturbation-Calibrated Uncertainty for Unsupervised Anomaly Detection
Mebarka Allaoui, Rachid Hedjam, Mohand Saïd Allili et al.
Contrastive Conformal Sets
Yahya Alkhatib, Wee Peng Tay
Distilling Safe LLM Systems via Soft Prompts for On Device Settings
Motasem Alfarra, Cristina Pinneri, Dana Kianfar et al.
Bridging Domain Invariance and Diversity: A Fine-Grained Risk Bound for Domain Generalization
Xi Wang, Liang Bai, Xian Yang et al.
High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks
Simon Martin, Giulio Biroli, Francis Bach
Error Analyses of Auto-Regressive Video Diffusion Models
Jing Wang, Fengzhuo Zhang, Xiaoli Li et al.
The Sample Complexity of Parameter-Free Stochastic Convex Optimization
Jared Lawrence, Ari Kalinsky, Hannah Bradfield et al.
End-to-End Deep Learning for Predicting Metric Space-Valued Outputs
Yidong Zhou, Su I Iao, Hans-Georg Müller
Graph-based Clustering Revisited: A Relaxation of Kernel k-Means Perspective
Wenlong Lyu, Yuheng Jia, Hui Liu et al.
Learning to Play Two-Player Perfect-Information Games without Knowledge
Quentin Cohen-Solal
Doubly Debiased Robust Subsampling for Transfer Learning
Tao Wang, Weng Kee Wong
Abstract Gradient Training: A Unified Certification Framework for Data Poisoning, Unlearning, and Differential Privacy
Philip Sosnin, Matthew Wicker, Josh Collyer et al.
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression
Filippo Ascolani, Giacomo Zanella
Underdamped Langevin MCMC with third order convergence
Maximilian Scott, Dáire O'Kane, Andraž Jelinčič et al.
Approximation-Free Differentiable Oblique Decision Trees
Subrat Prasad Panda, Blaise Genest, Arvind Easwaran
Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes
Ruiqi Zhang, Jingfeng Wu, Licong Lin et al.
Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes
Bohan Wu, Eli N. Weinstein, Sohrab Salehi et al.
Robust training of implicit generative models for multivariate and heavy-tailed distributions with an invariant statistical loss
José Manuel de Frutos, Manuel A. Vázquez, Pablo M. Olmos et al.
Gradient Span Algorithms Make Predictable Progress in High Dimension
Felix Benning, Leif Döring
py/cuTAGI: An Open-Source Library for Tractable Approximate Gaussian Inference in Bayesian Neural Networks
Luong-Ha Nguyen, James-A. Goulet, Miquel Florensa-Montilla et al.
Statistical Test for Attention in Transformers for Images and Time Series
Tomohiro Shiraishi, Daiki Miwa, Teruyuki Katsuoka et al.
Accelerating Constrained Sampling: A Large Deviations Approach
Yingli Wang, Changwei Tu, Xiaoyu Wang et al.