Papers
Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes
Zhiyuan Jerry Lin, Raul Astudillo, Peter Frazier et al.
Primal-Dual Stochastic Mirror Descent for MDPs
Daniil Tiapkin, Alexander Gasnikov
Privacy Amplification by Decentralization
Edwige Cyffers, Aurélien Bellet
Privacy Amplification by Subsampling in Time Domain
Tatsuki Koga, Casey Meehan, Kamalika Chaudhuri
Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size
Wanrong Zhang, Yajun Mei, Rachel Cummings
Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations
Nicholas Krämer, Jonathan Schmidt, Philipp Hennig
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods
Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju
Projection Predictive Inference for Generalized Linear and Additive Multilevel Models
Alejandro Catalina, Paul-Christian Bürkner, Aki Vehtari
Provable Adversarial Robustness for Fractional Lp Threat Models
Alexander J. Levine, Soheil Feizi
Provable Continual Learning via Sketched Jacobian Approximations
Reinhard Heckel
Provable Lifelong Learning of Representations
Xinyuan Cao, Weiyang Liu, Santosh Vempala
Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Games
Yulai Zhao, Yuandong Tian, Jason Lee et al.
Proximal Optimal Transport Modeling of Population Dynamics
Charlotte Bunne, Laetitia Papaxanthos, Andreas Krause et al.
Pulling back information geometry
Georgios Arvanitidis, Miguel González-Duque, Alison Pouplin et al.
QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning
Maxime Vono, Vincent Plassier, Alain Durmus et al.
Quadric Hypersurface Intersection for Manifold Learning in Feature Space
Fedor Pavutnitskiy, Sergei O. Ivanov, Evgeniy Abramov et al.
Random Effect Bandits
Rong Zhu, Branislav Kveton
Randomized Stochastic Gradient Descent Ascent
Othmane Sebbouh, Marco Cuturi, Gabriel Peyré
Rapid Convergence of Informed Importance Tempering
Quan Zhou, Aaron Smith
Reconstructing Test Labels from Noisy Loss Functions
Abhinav Aggarwal, Shiva Kasiviswanathan, Zekun Xu et al.
Recoverability Landscape of Tree Structured Markov Random Fields under Symmetric Noise
Ashish Katiyar, Soumya Basu, Vatsal Shah et al.
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
Hung Tran-The, Sunil Gupta, Santu Rana et al.
Regret, stability & fairness in matching markets with bandit learners
Sarah H. Cen, Devavrat Shah
Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi et al.
Rejection sampling from shape-constrained distributions in sublinear time
Sinho Chewi, Patrik R. Gerber, Chen Lu et al.