Optimization & Theory

Gated Recurrent Convolution Neural Network for OCR NeurIPS 2017 Generalized Conditional Gradient for Sparse Estimation JMLR 2017 Geometric Descent Method for Convex Composite Minimization NeurIPS 2017 Geometric Loss Functions for Camera Pose Regression With Deep Learning CVPR 2017 Global Optimality in Neural Network Training CVPR 2017 Gradient Descent Can Take Exponential Time to Escape Saddle Points NeurIPS 2017 Graph Matching via Multiplicative Update Algorithm NeurIPS 2017 Hash Embeddings for Efficient Word Representations NeurIPS 2017 HOPE: Hierarchical Object Prototype Encoding for Efficient Object Instance Search in Videos CVPR 2017 How regularization affects the critical points in linear networks NeurIPS 2017 Hyper-Laplacian Regularized Unidirectional Low-Rank Tensor Recovery for Multispectral Image Denoising CVPR 2017 Implicit Regularization in Matrix Factorization NeurIPS 2017 Improved Graph Laplacian via Geometric Self-Consistency NeurIPS 2017 Improved Training of Wasserstein GANs NeurIPS 2017 Improving Interpretability of Deep Neural Networks With Semantic Information CVPR 2017 Improving Training of Deep Neural Networks via Singular Value Bounding CVPR 2017 Input-to-Output Gate to Improve RNN Language Models IJCNLP 2017 Invariance and Stability of Deep Convolutional Representations NeurIPS 2017 Joint Training of Multi-Channel-Condition Dereverberation and Acoustic Modeling of Microphone Array Speech for Robust Distant Speech Recognition Interspeech 2017 Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NeurIPS 2017 Learning Adaptive Receptive Fields for Deep Image Parsing Network CVPR 2017 Learning ReLUs via Gradient Descent NeurIPS 2017 Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon NeurIPS 2017 Less than a Single Pass: Stochastically Controlled Stochastic Gradient AISTATS 2017 Limits of End-to-End Learning ACML 2017