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Machine Learning › Optimization & Theory ›

Neural Network Optimization

3,648 papers

Papers per year

Papers

MCR-Data2vec 2.0: Improving Self-supervised Speech Pre-training via Model-level Consistency Regularization INTERSPEECH 2023
An Efficient Speech Separation Network Based on Recurrent Fusion Dilated Convolution and Channel Attention INTERSPEECH 2023
Deeply Supervised Curriculum Learning for Deep Neural Network-based Sound Source Localization INTERSPEECH 2023
Rethinking the Visual Cues in Audio-Visual Speaker Extraction INTERSPEECH 2023
AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation INTERSPEECH 2023
Speaker-independent Speech Inversion for Estimation of Nasalance INTERSPEECH 2023
BAT: Boundary aware transducer for memory-efficient and low-latency ASR INTERSPEECH 2023
On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size JMLR 2023
Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval JMLR 2023
Decentralized Learning: Theoretical Optimality and Practical Improvements JMLR 2023
Sparse Training with Lipschitz Continuous Loss Functions and a Weighted Group L0-norm Constraint JMLR 2023
Deep linear networks can benignly overfit when shallow ones do JMLR 2023
Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks JMLR 2023
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification JMLR 2023
Learning an Explicit Hyper-parameter Prediction Function Conditioned on Tasks JMLR 2023
An Inexact Augmented Lagrangian Algorithm for Training Leaky ReLU Neural Network with Group Sparsity JMLR 2023
Improved Powered Stochastic Optimization Algorithms for Large-Scale Machine Learning JMLR 2023
Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks JMLR 2023
The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima JMLR 2023
TorchOpt: An Efficient Library for Differentiable Optimization JMLR 2023
On the Dynamics Under the Unhinged Loss and Beyond JMLR 2023
On Learning Rates and Schrödinger Operators JMLR 2023
Over-parameterized Deep Nonparametric Regression for Dependent Data with Its Applications to Reinforcement Learning JMLR 2023
A Unified Approach to Controlling Implicit Regularization via Mirror Descent JMLR 2023
Physics-Informed Model-Based Reinforcement Learning L4DC 2023