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Optimization & Theory

6,829 papers (27 classified directly here)

Subtopics

Model Compression (1,785) Optimization (1,664) Efficient Computing (1,579) Theory (1,082) Neural Network Optimization (903) Evaluation (509) Loss Functions (123) Interpretability (105) Stochastic Methods (97) Regularization (77) Generalization (24) Sparse Optimization (7)

Papers per year

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50
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Papers (including subtopics)

A Greedy Approach for Budgeted Maximum Inner Product Search NIPS 2017
Riemannian approach to batch normalization NIPS 2017
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee NIPS 2017
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data NIPS 2017
The Numerics of GANs NIPS 2017
SGD Learns the Conjugate Kernel Class of the Network NIPS 2017
Selective Classification for Deep Neural Networks NIPS 2017
SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks NIPS 2017
Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks NIPS 2017
Deep Hyperspherical Learning NIPS 2017
Implicit Regularization in Matrix Factorization NIPS 2017
SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud NIPS 2017
Improved Graph Laplacian via Geometric Self-Consistency NIPS 2017
Straggler Mitigation in Distributed Optimization Through Data Encoding NIPS 2017
Bayesian Compression for Deep Learning NIPS 2017
Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks NIPS 2017
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding NIPS 2017
Sobolev Training for Neural Networks NIPS 2017
Training Deep Networks without Learning Rates Through Coin Betting NIPS 2017
The Marginal Value of Adaptive Gradient Methods in Machine Learning NIPS 2017
Mean Field Residual Networks: On the Edge of Chaos NIPS 2017
Non-convex Finite-Sum Optimization Via SCSG Methods NIPS 2017
Improved Training of Wasserstein GANs NIPS 2017
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning NIPS 2017
An Empirical Study on The Properties of Random Bases for Kernel Methods NIPS 2017