Papers
On the Faster Alternating Least-Squares for CCA
Zhiqiang Xu, Ping Li
On the Generalization Properties of Adversarial Training
Yue Xing, Qifan Song, Guang Cheng
On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
Baohe Zhang, Raghu Rajan, Luis Pineda et al.
On the Linear Convergence of Policy Gradient Methods for Finite MDPs
Jalaj Bhandari, Daniel Russo
On the Memory Mechanism of Tensor-Power Recurrent Models
Hejia Qiu, Chao Li, Ying Weng et al.
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity
Yuuki Takai, Akiyoshi Sannai, Matthieu Cordonnier
On the Privacy Properties of GAN-generated Samples
Zinan Lin, Vyas Sekar, Giulia Fanti
On the proliferation of support vectors in high dimensions
Daniel Hsu, Vidya Muthukumar, Ji Xu
On the Role of Data in PAC-Bayes Bounds
Gintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh et al.
On the Suboptimality of Negative Momentum for Minimax Optimization
Guodong Zhang, Yuanhao Wang
Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy
Onur Teymur, Jackson Gorham, Marina Riabiz et al.
Optimal query complexity for private sequential learning against eavesdropping
Jiaming Xu, Kuang Xu, Dana Yang
Optimizing Percentile Criterion using Robust MDPs
Bahram Behzadian, Reazul Hasan Russel, Marek Petrik et al.
Parametric Programming Approach for More Powerful and General Lasso Selective Inference
Vo Nguyen Le Duy, Ichiro Takeuchi
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.