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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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Papers (including subtopics)

Efficient Adaptive Online Learning via Frequent Directions IJCAI 2018
On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization IJCAI 2018
Densely Connected Networks for Conversational Speech Recognition INTERSPEECH 2018
Conditional-Computation-Based Recurrent Neural Networks for Computationally Efficient Acoustic Modelling INTERSPEECH 2018
Single-Channel Dereverberation Using Direct MMSE Optimization and Bidirectional LSTM Networks INTERSPEECH 2018
Inference-Invariant Transformation of Batch Normalization for Domain Adaptation of Acoustic Models INTERSPEECH 2018
Temporal Noise Shaping with Companding INTERSPEECH 2018
Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks INTERSPEECH 2018
Gradient Estimation with Simultaneous Perturbation and Compressive Sensing JMLR 2018
Gradient Hard Thresholding Pursuit JMLR 2018
Local Identifiability of $\ell_1$-minimization Dictionary Learning: a Sufficient and Almost Necessary Condition JMLR 2018
Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning JMLR 2018
RSG: Beating Subgradient Method without Smoothness and Strong Convexity JMLR 2018
The Implicit Bias of Gradient Descent on Separable Data JMLR 2018
Pieces of Eight: 8-bit Neural Machine Translation NAACL 2018
On the Relative Expressiveness of Bayesian and Neural Networks PGM 2018
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NIPS 2017
Nonlinear random matrix theory for deep learning NIPS 2017
How regularization affects the critical points in linear networks NIPS 2017
Population Matching Discrepancy and Applications in Deep Learning NIPS 2017
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples NIPS 2017
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions NIPS 2017
Reducing Reparameterization Gradient Variance NIPS 2017
The Expressive Power of Neural Networks: A View from the Width NIPS 2017
Invariance and Stability of Deep Convolutional Representations NIPS 2017