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07/14/2023
Multimodal Distillation for Egocentric Action Recognition
The focal point of egocentric video understanding is modelling hand-obje...
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05/15/2023
Document Understanding Dataset and Evaluation (DUDE)
We call on the Document AI (DocAI) community to reevaluate current metho...
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10/09/2022
Students taught by multimodal teachers are superior action recognizers
The focal point of egocentric video understanding is modelling hand-obje...
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12/10/2021
Predicting Physical World Destinations for Commands Given to Self-Driving Cars
In recent years, we have seen significant steps taken in the development...
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12/01/2021
Differentially Private SGD with Sparse Gradients
To protect sensitive training data, differentially private stochastic gr...
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10/15/2020
R-GAP: Recursive Gradient Attack on Privacy
Federated learning frameworks have been regarded as a promising approach...
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09/18/2020
Commands 4 Autonomous Vehicles (C4AV) Workshop Summary
The task of visual grounding requires locating the most relevant region ...
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03/04/2020
Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs
Knee osteoarthritis (OA) is one of the highest disability factors in the...
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11/05/2019
Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory Practice
The Dice score and Jaccard index are commonly used metrics for the evalu...
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03/11/2019
Generating superpixels using deep image representations
Superpixel algorithms are a common pre-processing step for computer visi...
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09/17/2018
Scattering Networks for Hybrid Representation Learning
Scattering networks are a class of designed Convolutional Neural Network...
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05/20/2016
Learning to Discover Sparse Graphical Models
We consider structure discovery of undirected graphical models from obse...
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04/12/2016
A Convex Surrogate Operator for General Non-Modular Loss Functions
Empirical risk minimization frequently employs convex surrogates to unde...
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04/06/2016
A U-statistic Approach to Hypothesis Testing for Structure Discovery in Undirected Graphical Models
Structure discovery in graphical models is the determination of the topo...
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12/24/2015
The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses
Learning with non-modular losses is an important problem when sets of pr...
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07/08/2013
B-tests: Low Variance Kernel Two-Sample Tests
A family of maximum mean discrepancy (MMD) kernel two-sample tests is in...
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06/21/2013