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1611.01838
Cited By
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
6 November 2016
Pratik Chaudhari
A. Choromańska
Stefano Soatto
Yann LeCun
Carlo Baldassi
C. Borgs
J. Chayes
Levent Sagun
R. Zecchina
ODL
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Papers citing
"Entropy-SGD: Biasing Gradient Descent Into Wide Valleys"
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Title
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Effective Gradient Sample Size via Variation Estimation for Accelerating Sharpness aware Minimization
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Ali Jadbabaie
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Randomized Adversarial Training via Taylor Expansion
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Rethinking Confidence Calibration for Failure Prediction
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SAM operates far from home: eigenvalue regularization as a dynamical phenomenon
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Yann N. Dauphin
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The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems
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The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
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Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning
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Stability Analysis of Sharpness-Aware Minimization
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Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data
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Sumukh K Aithal
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KL Regularized Normalization Framework for Low Resource Tasks
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Non-reversible Parallel Tempering for Deep Posterior Approximation
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Symmetries, flat minima, and the conserved quantities of gradient flow
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Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
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ROSE: Robust Selective Fine-tuning for Pre-trained Language Models
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Jie Zhou
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The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima
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Learning Gradient-based Mixup towards Flatter Minima for Domain Generalization
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A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases
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Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning
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Qi Chen
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Mengjie Zhang
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FS-BAN: Born-Again Networks for Domain Generalization Few-Shot Classification
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On Leave-One-Out Conditional Mutual Information For Generalization
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Sparse Double Descent: Where Network Pruning Aggravates Overfitting
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Generalized Federated Learning via Sharpness Aware Minimization
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Information-Theoretic Odometry Learning
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