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04/11/2023
The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
No free lunch theorems for supervised learning state that no learner can...
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12/13/2022
What do Vision Transformers Learn? A Visual Exploration
Vision transformers (ViTs) are quickly becoming the de-facto architectur...
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10/23/2022
K-SAM: Sharpness-Aware Minimization at the Speed of SGD
Sharpness-Aware Minimization (SAM) has recently emerged as a robust tech...
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04/06/2022
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
Neural network classifiers can largely rely on simple spurious features,...
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06/15/2020
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Detecting out-of-distribution (OOD) data is crucial for robust machine l...
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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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02/11/2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
The posteriors over neural network weights are high dimensional and mult...
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09/28/2018
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
Despite advances in scalable models, the inference tools used for Gaussi...
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03/16/2018
Constant-Time Predictive Distributions for Gaussian Processes
One of the most compelling features of Gaussian process (GP) regression ...
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03/03/2015
