Papers
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
Alexander Lew, Monica Agrawal, David Sontag et al.
Power of Hints for Online Learning with Movement Costs
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar et al.
Prediction with Finitely many Errors Almost Surely
Changlong Wu, Narayana Santhanam
Predictive Complexity Priors
Eric Nalisnick, Jonathan Gordon, Jose Miguel Hernandez-Lobato
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation
Yue Xing, Qifan Song, Guang Cheng
Principal Component Regression with Semirandom Observations via Matrix Completion
Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena
Principal Subspace Estimation Under Information Diffusion
Fan Zhou, Ping Li, Zhixin Zhou
Private optimization without constraint violations
Andres Munoz, Umar Syed, Sergei Vassilvtiskii et al.
Probabilistic Sequential Matrix Factorization
Omer Deniz Akyildiz, Gerrit van den Burg, Theodoros Damoulas et al.
Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits
Avishek Ghosh, Abishek Sankararaman, Ramchandran Kannan
Product Manifold Learning
Sharon Zhang, Amit Moscovich, Amit Singer
Projection-Free Optimization on Uniformly Convex Sets
Thomas Kerdreux, Alexandre d’Aspremont, Sebastian Pokutta
Provable Hierarchical Imitation Learning via EM
Zhiyu Zhang, Ioannis Paschalidis
Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case
Yufeng Zhang, Zhuoran Yang, Zhaoran Wang
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
Dongsheng Ding, Xiaohan Wei, Zhuoran Yang et al.
Provably Safe PAC-MDP Exploration Using Analogies
Melrose Roderick, Vaishnavh Nagarajan, Zico Kolter
Q-learning with Logarithmic Regret
Kunhe Yang, Lin Yang, Simon Du
Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models
Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller et al.
Random Coordinate Underdamped Langevin Monte Carlo
Zhiyan Ding, Qin Li, Jianfeng Lu et al.
RankDistil: Knowledge Distillation for Ranking
Sashank Reddi, Rama Kumar Pasumarthi, Aditya Menon et al.
Rao-Blackwellised parallel MCMC
Tobias Schwedes, Ben Calderhead
Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization
Zichong Li, Pin-Yu Chen, Sijia Liu et al.
Rate-Regularization and Generalization in Variational Autoencoders
Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan et al.