Papers
Quantized Stochastic Primal–Dual Methods for Distributed Optimization under Relaxed Global Geometry
Susmit Sarkar, Abhinav Raghuvanshi, Kushal Chakrabarti et al.
Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models
Colin Samplawski, Ramneet Kaur, Manoj Acharya et al.
Variance Reduction for Non-Log-Concave Sampling with Applications to Inverse Problems
M. Berk Sahin, Ahmet Ege Tanriverdi, Behzad Sharif et al.
Fairness Uncertainty Quantification: A Constrained Stochastic Optimization Perspective
Abhishek Roy, Prasant Mohapatra
VaSST: Variational Inference for Symbolic Regression using Soft Symbolic Trees
Somjit Roy, Pritam Dey, Bani Mallick
Kernel Integrated R^2: A Measure of Dependence
Pouya Roudaki, Shakeel Gavioli-Akilagun, Florian Kalinke et al.
Constrained Weighted Bayesian Bootstrap
Sam Rosen, Jason Xu
Planning with Formal Reachability Guarantees in Goal-Oriented MDPs with Dead-Ends
Matisse Roche, Caroline P.C. Chanel, Yoko Watanabe
Imprecise Probabilities for Privacy–Accuracy Trade-offs in Bayesian Networks
Niccolò Rocchi, Fabio Stella, Cassio de Campos
Expert Advice with Costly Observations
Lev Reyzin, Aadirupa Saha, Shuo Wu
Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means
Raphaël Razafindralambo, Rémy Sun, Damien Garreau et al.
Structure Learning for Unfaithful Distributions: The Minimal Dependence Faithfulness
Pouria Ramazi, Hamid Kalantari
Variance Estimation and Selecting Good Estimands for Causal Effect Queries
Anna K Raichev, Rina Dechter, Jin Tian et al.
Metacognitive Arbitration as Uncertainty Compression in Multi-Agent Language Models
Mafizur Rahman, Lijun Qian
Beyond Mean-Field: Tree-Copula Variational Autoencoders for Structured Latent Dependencies
Yarden Rachamim, Shai Fine
Multi-Agent RL with Invisible Collaborators: Marginal Advantage Estimation for Indirect Cooperation
Jianglin Qiao, Zehong Cao, Siyi Hu et al.
Reading As Humans: Unified Negation Detection via Cascade Linear Attention Network with Model-Agnostic Meta-Learning
Zhong Qian, Peifeng Li, Qiaoming Zhu et al.
Transformer Based Bayesian Network Structure Learning from an Information Theory Perspective
Zhiwei Qi, Kun Yue, Zhu Yang et al.
Distributional Deep Gaussian Processes
Sebastian Popescu
UnGuide: Learning to Forget with LoRA-Guided Diffusion Models
Alicja Polowczyk, Agnieszka Polowczyk, Dawid Malarz et al.
A Characterization of the Orthocomplement of the Tangent Space of Semiparametric Markov Models
Trung Q. Phung, Ilya Shpitser
Semantic Self-Distillation for Language Model Uncertainty
Edward Phillips, Sean Wu, Fredrik K. Gustafsson et al.
Bayesian Experimental Design via Score Matching
Angus Phillips, Gavin Kerrigan, Tom Rainforth
How Predicted Links Influence Network Evolution: Disentangling Choice and Algorithmic Feedback in Dynamic Graphs
Mathilde Perez, Raphaël Romero, Jefrey Lijffijt et al.
Information Theoretic Bayesian Optimization over the Probability Simplex
Federico Pavesi, Antonio Candelieri, Noémie Jaquier