Papers
938 papers found
$E(2)$-Equivariant Vision Transformer
Renjun Xu, Kaifan Yang, Ke Liu et al.
A Bayesian approach for bandit online optimization with switching cost
Zai Shi, Jian Tan, Feifei Li
Accelerating Voting by Quantum Computation
Ao Liu, Qishen Han, Lirong Xia et al.
A constrained Bayesian approach to out-of-distribution prediction
Ziyu Wang, Binjie Yuan, Jiaxun Lu et al.
Active metric learning and classification using similarity queries
Namrata Nadagouda, Austin Xu, Mark A. Davenport
Adaptive Conditional Quantile Neural Processes
Peiman Mohseni, Nick Duffield, Bani Mallick et al.
Adaptivity Complexity for Causal Graph Discovery
Davin Choo, Kirankumar Shiragur
A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models
Sinong Geng, Houssam Nassif, Carlos A. Manzanares
A decoder suffices for query-adaptive variational inference
Sakshi Agarwal, Gabriel Hope, Ali Younis et al.
Aligned Diffusion Schrödinger Bridges
Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh et al.
Amortized Inference for Gaussian Process Hyperparameters of Structured Kernels
Matthias Bitzer, Mona Meister, Christoph Zimmer
A near-optimal high-probability swap-Regret upper bound for multi-agent bandits in unknown general-sum games
Zhiming Huang, Jianping Pan
An effective negotiating agent framework based on deep offline reinforcement learning
Siqi Chen, Jianing Zhao, Gerhard Weiss et al.
An improved variational approximate posterior for the deep Wishart process
Sebastian W. Ober, Ben Anson, Edward Milsom et al.
A one-sample decentralized proximal algorithm for non-convex stochastic composite optimization
Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian et al.
A policy gradient approach for optimization of smooth risk measures
Nithia Vijayan, L. A. Prashanth
Approximately Bayes-optimal pseudo-label selection
Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti et al.
Approximate Thompson Sampling via Epistemic Neural Networks
Ian Osband, Zheng Wen, Seyed Mohammad Asghari et al.
Approximating probabilistic explanations via supermodular minimization
Louenas Bounia, Frederic Koriche
A scalable Walsh-Hadamard regularizer to overcome the low-degree spectral bias of neural networks
Ali Gorji, Andisheh Amrollahi, Andreas Krause
Assessing the Impact of Context Inference Error and Partial Observability on RL Methods for Just-In-Time Adaptive Interventions
Karine Karine, Predrag Klasnja, Susan A. Murphy et al.
ASTRA: Understanding the practical impact of robustness for probabilistic programs
Zixin Huang, Saikat Dutta, Sasa Misailovic
A trajectory is worth three sentences: multimodal transformer for offline reinforcement learning
Yiqi Wang, Mengdi Xu, Laixi Shi et al.
AUC Maximization in Imbalanced Lifelong Learning
Xiangyu Zhu, Jie Hao, Yunhui Guo et al.
Bandits with costly reward observations
Aaron D. Tucker, Caleb Biddulph, Claire Wang et al.