Stochastic Methods

Fraunhofer IAIS at FinCausal 2020, Tasks 1 & 2: Using Ensemble Methods and Sequence Tagging to Detect Causality in Financial Documents COLING 2020 Generalized Nonbacktracking Bounds on the Influence JMLR 2020 How Good is SGD with Random Shuffling? COLT 2020 Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach AAAI 2020 Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020 Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks ICML 2020 Large-Scale Methods for Distributionally Robust Optimization NeurIPS 2020 Learning Behaviors with Uncertain Human Feedback UAI 2020 Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect UAI 2020 Learning to Crawl AAAI 2020 Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NeurIPS 2020 Linear bandits with Stochastic Delayed Feedback ICML 2020 Linear Convergence of Adaptive Stochastic Gradient Descent AISTATS 2020 Locally Differentially Private (Contextual) Bandits Learning NeurIPS 2020 Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo COLT 2020 Lookahead-Bounded Q-learning ICML 2020 Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks ICML 2020 Low-Variance and Zero-Variance Baselines for Extensive-Form Games ICML 2020 Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution AAAI 2020 Memoryless Sequences for General Losses JMLR 2020 Moniqua: Modulo Quantized Communication in Decentralized SGD ICML 2020 Monte-Carlo Graph Search: the Value of Merging Similar States ACML 2020 Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization ICML 2020 On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning ICLR 2020 Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach ICLR 2020