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Optimization

14,983 papers

Papers per year

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Papers

PiRank: Scalable Learning To Rank via Differentiable Sorting NIPS 2021
Best-case lower bounds in online learning NIPS 2021
A Comprehensively Tight Analysis of Gradient Descent for PCA NIPS 2021
On Robust Optimal Transport: Computational Complexity and Barycenter Computation NIPS 2021
On the Bias-Variance-Cost Tradeoff of Stochastic Optimization NIPS 2021
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization NIPS 2021
Twice regularized MDPs and the equivalence between robustness and regularization NIPS 2021
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks NIPS 2021
Pseudo-Spherical Contrastive Divergence NIPS 2021
Bandits with many optimal arms NIPS 2021
NAS-Bench-x11 and the Power of Learning Curves NIPS 2021
Observation-Free Attacks on Stochastic Bandits NIPS 2021
Fast Extra Gradient Methods for Smooth Structured Nonconvex-Nonconcave Minimax Problems NIPS 2021
Sparse Flows: Pruning Continuous-depth Models NIPS 2021
On the Rate of Convergence of Regularized Learning in Games: From Bandits and Uncertainty to Optimism and Beyond NIPS 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds NIPS 2021
Coresets for Time Series Clustering NIPS 2021
Does Preprocessing Help Training Over-parameterized Neural Networks? NIPS 2021
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization NIPS 2021
Minibatch and Momentum Model-based Methods for Stochastic Weakly Convex Optimization NIPS 2021
Bandits with Knapsacks beyond the Worst Case NIPS 2021
Meta-learning to Improve Pre-training NIPS 2021
Adaptive Diffusion in Graph Neural Networks NIPS 2021
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization NIPS 2021
Fast Approximate Dynamic Programming for Infinite-Horizon Markov Decision Processes NIPS 2021