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08/30/2023
Domain Generalization without Excess Empirical Risk
Given data from diverse sets of distinct distributions, domain generaliz...
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08/18/2023
Generalized Sum Pooling for Metric Learning
A common architectural choice for deep metric learning is a convolutiona...
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07/26/2023
Simulation-based Inference for Cardiovascular Models
Over the past decades, hemodynamics simulators have steadily evolved and...
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05/16/2023
Online Continual Learning Without the Storage Constraint
Online continual learning (OCL) research has primarily focused on mitiga...
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11/27/2022
Generalizing Gaussian Smoothing for Random Search
Gaussian smoothing (GS) is a derivative-free optimization (DFO) algorith...
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10/12/2022
Improving information retention in large scale online continual learning
Given a stream of data sampled from non-stationary distributions, online...
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12/27/2021
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation
We present MSeg, a composite dataset that unifies semantic segmentation ...
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08/20/2021
Online Continual Learning with Natural Distribution Shifts: An Empirical Study with Visual Data
Continual learning is the problem of learning and retaining knowledge th...
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10/24/2020
Modeling and Optimization Trade-off in Meta-learning
By searching for shared inductive biases across tasks, meta-learning pro...
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07/18/2020
Drinking from a Firehose: Continual Learning with Web-scale Natural Language
Continual learning systems will interact with humans, with each other, a...
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06/16/2020
Hausdorff Dimension, Stochastic Differential Equations, and Generalization in Neural Networks
Despite its success in a wide range of applications, characterizing the ...
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04/25/2020
Learning to Guide Random Search
We are interested in derivative-free optimization of high-dimensional fu...
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01/27/2020
rCRF: Recursive Belief Estimation over CRFs in RGB-D Activity Videos
For assistive robots, anticipating the future actions of humans is an es...
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01/27/2020
Learning Transferrable Representations for Unsupervised Domain Adaptation
Supervised learning with large scale labelled datasets and deep layered ...
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10/10/2018
Multi-Task Learning as Multi-Objective Optimization
In multi-task learning, multiple tasks are solved jointly, sharing induc...
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05/30/2018
Generalizing to Unseen Domains via Adversarial Data Augmentation
We are concerned with learning models that generalize well to different ...
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05/29/2018
Deep Learning under Privileged Information Using Heteroscedastic Dropout
Unlike machines, humans learn through rapid, abstract model-building. Th...
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08/01/2017
Active Learning for Convolutional Neural Networks: A Core-Set Approach
Convolutional neural networks (CNNs) have been successfully applied to m...
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05/11/2016
Unsupervised Semantic Action Discovery from Video Collections
Human communication takes many forms, including speech, text and instruc...
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03/11/2016
Watch-n-Patch: Unsupervised Learning of Actions and Relations
There is a large variation in the activities that humans perform in thei...
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02/10/2016
Unsupervised Transductive Domain Adaptation
Supervised learning with large scale labeled datasets and deep layered m...
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06/28/2015
Unsupervised Semantic Parsing of Video Collections
Human communication typically has an underlying structure. This is refle...
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12/01/2014
RoboBrain: Large-Scale Knowledge Engine for Robots
In this paper we introduce a knowledge engine, which learns and shares k...
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01/22/2013