Papers
How PC-based Methods Err: Towards Better Reporting of Assumption Violations and Small Sample Errors
Sofia Faltenbacher, Jonas Wahl, Rebecca Jean Herman et al.
One Model to Rule Them All: Canonically Gluing Causal Models Along Shared Substructures
Markus Englberger, Devendra Singh Dhami
Neural Diffusion Intensity Models for Point Process Data
Xinlong Du, Harsha Honnappa, Vinayak Rao
Sparse Action-Dependent Policy Iteration under Coordination Structures: Convergence and Optimality
Jianglin Ding, Jingcheng Tang, Gangshan Jing
Communication-Efficient Distributed Training for Collaborative Flat Optima Recovery in Deep Learning
Tolga Dimlioglu, Anna Ewa Choromanska
Ensemble Diversity Optimization for Subjective Supervision
Xia Cui, Ziyi Huang, Nishanthi Rupika Abeynayake
Which Directions Matter? Sparse Design for Affine Robust Optimization
Pedro Chumpitaz-Flores, My Duong, Juan S. Borrero et al.
Canonical Domain Reduction for Partial Counterfactual Identification
Yesong Choe, Yeahoon Kwon, Min Woo Park et al.
Policy Optimization for Adversarial Linear Mixture MDPs with Unknown Transitions and Bandit Feedback
Yutian Cheng, Canzhe Zhao, Shuai Li
Hyperbolic Belief Propagation
Zehua Cheng, Wei Dai, Jiahao Sun
On the Sublinear Regret of Continuous K-Max Bandits
Yu Chen, Siwei Wang, Longbo Huang et al.
On the Granularity of Causal Effect Identifiability
Yizuo Chen, Adnan Darwiche
Finite-Sample Regret Analysis of Nash Q-Learning with Random-Feature Approximation
Yongshan Chen, Yuchen Hou, Zhuowen Zou et al.
Interactive Multi-Objective Probabilistic Preference Learning with Soft and Hard Bounds
Edward Chen, Sang T. Truong, Natalie Dullerud et al.
SteinGate: Tail-Sensitive Safe Reinforcement Learning via Stein Discrepancy
Yassine Chemingui, Chenhua Fan, Honghao Wei et al.
Linear Regression with Heteroskedastic Errors
Siddhant Chaudhary, Aditya Bhaskara
Inference for quantile-parametrized families via CDF confidence bands
Srijan Chattopadhyay, Siddhaarth Sarkar, Arun K. Kuchibhotla
Robust Constrained Markov Games: Multi-Agent Decision-Making under Model Uncertainty and Constraints
Ningkang Chang, Chenyu Xu, Ziying Jia et al.
Group-Fair Allocations of Contiguous Blocks of Indivisible Items
Hau Chan, Minming Li, Yingchao Zhao et al.
Neural Routed Boosting: Robust Learning against Heteroscedastic Noise
Puspak Chakraborty, Arun Rajkumar
Robust Predictive Uncertainty and Double Descent in Contaminated Bayesian Random Features
Michele Caprio, Katerina Papagiannouli, Siu Lun Chau et al.
Provably Efficient Personalized Multi-Objective Bandits with Proactive Conversational Queries
Linfeng Cao, Ming Shi, Ness Shroff
An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression
Christopher Bülte, Yusuf Sale, Timo Löhr et al.
Uncertainty Quantification for Regression: A Unified Framework based on kernel scores
Christopher Bülte, Yusuf Sale, Gitta Kutyniok et al.