conftrace_

neural network optimization

1293 papers

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Co-occurring keywords

model compression (3302) neural network (6616) convolutional neural network (4226) gradient descent (1144) stochastic gradient descent (1091) efficient computing (781) deep neural network (1803) large language model (13587) knowledge distillation (3725) representation learning (6206)

Papers

Hyperparameter Optimization for Tracking With Continuous Deep Q-Learning CVPR 2018
Understanding Generalization and Optimization Performance of Deep CNNs ICML 2018
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks ICML 2018
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks ICML 2018
Spotlight: Optimizing Device Placement for Training Deep Neural Networks ICML 2018
The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks CVPR 2018
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning CVPR 2018
Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima ICML 2018
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries NIPS 2018
Failures of Gradient-Based Deep Learning ICML 2017
Compression-aware Training of Deep Networks NIPS 2017
An experimental analysis of Noise-Contrastive Estimation: the noise distribution matters EACL 2017
Learning ReLUs via Gradient Descent NIPS 2017
On-the-fly Operation Batching in Dynamic Computation Graphs NIPS 2017
All You Need Is Beyond a Good Init: Exploring Better Solution for Training Extremely Deep Convolutional Neural Networks With Orthonormality and Modulation CVPR 2017
CTC in the Context of Generalized Full-Sum HMM Training INTERSPEECH 2017
Learning Gradient Descent: Better Generalization and Longer Horizons ICML 2017
Improving Training of Deep Neural Networks via Singular Value Bounding CVPR 2017
On the Flatness of Loss Surface for Two-layered ReLU Networks ACML 2017
Decoupled Neural Interfaces using Synthetic Gradients ICML 2017
Automated Curriculum Learning for Neural Networks ICML 2017
On Blackbox Backpropagation and Jacobian Sensing NIPS 2017
Learning RBM with a DC programming Approach ACML 2017
Accumulated Gradient Normalization ACML 2017
Neural Networks and Rational Functions ICML 2017