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Stochastic Methods

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Subset Selection by Pareto Optimization with Recombination AAAI 2020
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization AAAI 2020
An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint AAAI 2020
A Stochastic Derivative-Free Optimization Method with Importance Sampling: Theory and Learning to Control AAAI 2020
Robust Gradient-Based Markov Subsampling AAAI 2020
TellTail: Fast Scoring and Detection of Dense Subgraphs AAAI 2020
Improved Subsampled Randomized Hadamard Transform for Linear SVM AAAI 2020
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs AAAI 2020
Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function NIPS 2020
Dual Instrumental Variable Regression NIPS 2020
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty UAI 2020
Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach AAAI 2020
Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting AAAI 2020
Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy AAAI 2020
Reinforcement Learning of Risk-Constrained Policies in Markov Decision Processes AAAI 2020
Finite Continuum-Armed Bandits NIPS 2020
One Sample Stochastic Frank-Wolfe AISTATS 2020
A Duality Approach for Regret Minimization in Average-Award Ergodic Markov Decision Processes L4DC 2020
Dual Stochastic MPC for Systems with Parametric and Structural Uncertainty L4DC 2020
Tensorized Random Projections AISTATS 2020
Near-optimal Regret Bounds for Stochastic Shortest Path ICML 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems ICML 2020
Auto-Tuning Structured Light by Optical Stochastic Gradient Descent CVPR 2020
Optimal Private Median Estimation under Minimal Distributional Assumptions NIPS 2020