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Optimization

341 directly classified papers

Papers per year

Papers

Concurrency Debugging with MaxSMT AAAI 2019
No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms NIPS 2019
Efficient Optimal Approximation of Discrete Random Variables for Estimation of Probabilities of Missing Deadlines AAAI 2019
Gradient Harmonized Single-Stage Detector AAAI 2019
A Genetic Algorithm for Finding a Small and Diverse Set of Recent News Stories on a Given Subject: How We Generate AAAI’s AI-Alert AAAI 2019
Momentum-Based Variance Reduction in Non-Convex SGD NIPS 2019
Variance Reduction in Bipartite Experiments through Correlation Clustering NIPS 2019
RSN: Randomized Subspace Newton NIPS 2019
Iterative Least Trimmed Squares for Mixed Linear Regression NIPS 2019
Dimension-Free Bounds for Low-Precision Training NIPS 2019
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data NIPS 2019
Massively scalable Sinkhorn distances via the Nyström method NIPS 2019
HyperAdam: A Learnable Task-Adaptive Adam for Network Training AAAI 2019
Asymmetric Valleys: Beyond Sharp and Flat Local Minima NIPS 2019
How degenerate is the parametrization of neural networks with the ReLU activation function? NIPS 2019
Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent NIPS 2019
Adaptive Online Learning in Dynamic Environments NIPS 2018
Efficient online algorithms for fast-rate regret bounds under sparsity NIPS 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator NIPS 2018
Deep Dynamical Modeling and Control of Unsteady Fluid Flows NIPS 2018
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance NIPS 2018
Global Non-convex Optimization with Discretized Diffusions NIPS 2018
Learning to Teach with Dynamic Loss Functions NIPS 2018
Benefits of over-parameterization with EM NIPS 2018
Adaptive Methods for Nonconvex Optimization NIPS 2018