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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)

KCNN: Kernel-wise Quantization to Remarkably Decrease Multiplications in Convolutional Neural Network IJCAI 2019
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance IJCAI 2019
Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses IJCAI 2019
A Dual Approach to Verify and Train Deep Networks IJCAI 2019
Learning in the Machine: Random Backpropagation and the Deep Learning Channel (Extended Abstract) IJCAI 2019
Transformer Dissection: An Unified Understanding for Transformer’s Attention via the Lens of Kernel IJCNLP 2019
Improving Keyword Spotting and Language Identification via Neural Architecture Search at Scale INTERSPEECH 2019
Whether to Pretrain DNN or not?: An Empirical Analysis for Voice Conversion INTERSPEECH 2019
MobiLipNet: Resource-Efficient Deep Learning Based Lipreading INTERSPEECH 2019
End-to-End Optimization of Source Models for Speech and Audio Coding Using a Machine Learning Framework INTERSPEECH 2019
Optimizing a Speaker Embedding Extractor Through Backend-Driven Regularization INTERSPEECH 2019
Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression JMLR 2019
Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery JMLR 2019
Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes JMLR 2019
Stochastic Variance-Reduced Cubic Regularization Methods JMLR 2019
One-Shot Marginal MAP Inference in Markov Random Fields UAI 2019
Truly Proximal Policy Optimization UAI 2019
Towards a Better Understanding and Regularization of GAN Training Dynamics UAI 2019
Efficient Neural Network Verification with Exactness Characterization UAI 2019
Learnability for the Information Bottleneck UAI 2019
Computing Higher Order Derivatives of Matrix and Tensor Expressions NIPS 2018
Implicit Bias of Gradient Descent on Linear Convolutional Networks NIPS 2018
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries NIPS 2018
Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes NIPS 2018
Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms NIPS 2018