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Methodology
← Optimization
Mathematics & Optimization
›
Optimization
›
Stochastic Methods
2788 directly classified papers
Papers per year
2000: 1
2002: 2
2003: 5
2004: 1
2005: 2
2006: 10
2007: 13
2008: 16
2009: 15
2010: 23
2011: 33
2012: 43
2013: 69
2014: 77
2015: 82
2016: 112
2017: 144
2018: 173
2019: 265
2020: 292
2021: 316
2022: 314
2023: 353
2024: 307
2025: 98
2026: 22
Papers
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
NIPS 2021
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum
NIPS 2021
Integrated Optimization of Bipartite Matching and Its Stochastic Behavior: New Formulation and Approximation Algorithm via Min-cost Flow Optimization
AAAI 2021
Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling
AAAI 2021
Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently
AAAI 2021
Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization
AAAI 2021
Online Non-Monotone DR-Submodular Maximization
AAAI 2021
A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method
AAAI 2021
Anytime Heuristic and Monte Carlo Methods for Large-Scale Simultaneous Coalition Structure Generation and Assignment
AAAI 2021
Robust Finite-State Controllers for Uncertain POMDPs
AAAI 2021
Escaping Local Optima with Non-Elitist Evolutionary Algorithms
AAAI 2021
Rejection Sampling for Weighted Jaccard Similarity Revisited
AAAI 2021
Theoretical Analyses of Multi-Objective Evolutionary Algorithms on Multi-Modal Objectives
AAAI 2021
Robust Contextual Bandits via Bootstrapping
AAAI 2021
Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities
AAAI 2021
Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods
CVPR 2021
Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence
NIPS 2021
Information-constrained optimization: can adaptive processing of gradients help?
NIPS 2021
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning
NIPS 2021
Differentiable Quality Diversity
NIPS 2021
An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives
NIPS 2021
Adapting to function difficulty and growth conditions in private optimization
NIPS 2021
Estimating High Order Gradients of the Data Distribution by Denoising
NIPS 2021
A Sharp Leap from Quantified Boolean Formula to Stochastic Boolean Satisfiability Solving
AAAI 2021
Disjunctive Temporal Problems under Structural Restrictions
AAAI 2021
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