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Methodology
← Optimization & Theory
Machine Learning
›
Optimization & Theory
›
Stochastic Methods
1077 directly classified papers
Papers per year
2005: 2
2006: 5
2007: 7
2008: 12
2009: 6
2010: 18
2011: 18
2012: 29
2013: 28
2014: 38
2015: 33
2016: 37
2017: 44
2018: 58
2019: 78
2020: 102
2021: 117
2022: 126
2023: 117
2024: 156
2025: 43
2026: 3
Papers
RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization
AISTATS 2020
Linear Convergence of Adaptive Stochastic Gradient Descent
AISTATS 2020
Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes
AISTATS 2020
Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects
CORL 2020
Monte-Carlo Graph Search: the Value of Merging Similar States
ACML 2020
Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond
AAAI 2020
Learning to Crawl
AAAI 2020
The Error-Feedback framework: SGD with Delayed Gradients
JMLR 2020
A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound
AAAI 2020
Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations
AAAI 2020
Delay-Adaptive Distributed Stochastic Optimization
AAAI 2020
Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations
NIPS 2020
Debiasing Averaged Stochastic Gradient Descent to handle missing values
NIPS 2020
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot
NIPS 2020
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
NIPS 2019
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron
AISTATS 2019
Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization
IJCAI 2019
Scalable Semi-Supervised SVM via Triply Stochastic Gradients
IJCAI 2019
Randomized Iterative Algorithms for Fisher Discriminant Analysis
UAI 2019
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
UAI 2019
Periodic Kernel Approximation by Index Set Fourier Series Features
UAI 2019
Problem-dependent Regret Bounds for Online Learning with Feedback Graphs
UAI 2019
On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits
UAI 2019
Generating and Sampling Orbits for Lifted Probabilistic Inference
UAI 2019
Off-Policy Policy Gradient with Stationary Distribution Correction
UAI 2019
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