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10/04/2022
CADet: Fully Self-Supervised Anomaly Detection With Contrastive Learning
Handling out-of-distribution (OOD) samples has become a major stake in t...
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10/28/2021
Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize
We investigate the convergence of stochastic mirror descent (SMD) in rel...
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10/26/2020
LEAD: Least-Action Dynamics for Min-Max Optimization
Adversarial formulations such as generative adversarial networks (GANs) ...
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11/03/2019
Adversarial target-invariant representation learning for domain generalization
In many applications of machine learning, the training and test set data...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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10/19/2018
A Modern Take on the Bias-Variance Tradeoff in Neural Networks
We revisit the bias-variance tradeoff for neural networks in light of mo...
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10/06/2018
h-detach: Modifying the LSTM Gradient Towards Better Optimization
Recurrent neural networks are known for their notorious exploding and va...
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06/12/2017
YellowFin and the Art of Momentum Tuning
Hyperparameter tuning is one of the big costs of deep learning. State-of...
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05/31/2016
