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06/22/2023
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation
We develop an approach to efficiently grow neural networks, within which...
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05/31/2023
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits
Proper evaluations are crucial for better understanding, troubleshooting...
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12/14/2020
Information-Theoretic Segmentation by Inpainting Error Maximization
We study image segmentation from an information-theoretic perspective, p...
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12/05/2020
Self-Supervised Visual Representation Learning from Hierarchical Grouping
We create a framework for bootstrapping visual representation learning f...
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11/23/2020
Boosting Contrastive Self-Supervised Learning with False Negative Cancellation
Self-supervised representation learning has witnessed significant leaps ...
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08/15/2020
Orthogonalized SGD and Nested Architectures for Anytime Neural Networks
We propose a novel variant of SGD customized for training network archit...
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07/30/2020
Growing Efficient Deep Networks by Structured Continuous Sparsification
We develop an approach to training deep networks while dynamically adjus...
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04/04/2020
Pixel Consensus Voting for Panoptic Segmentation
The core of our approach, Pixel Consensus Voting, is a framework for ins...
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12/10/2019
Winning the Lottery with Continuous Sparsification
The Lottery Ticket Hypothesis from Frankle Carbin (2019) conjectures...
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12/04/2019
Domain-independent Dominance of Adaptive Methods
From a simplified analysis of adaptive methods, we derive AvaGrad, a new...
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10/31/2019
ALERT: Accurate Learning for Energy and Timeliness
An increasing number of software applications incorporate runtime Deep N...
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10/31/2019
ALERT: Accurate Anytime Learning for Energy and Timeliness
An increasing number of software applications incorporate runtime Deep N...
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06/13/2019
Multigrid Neural Memory
We introduce a novel architecture that integrates a large addressable me...
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02/26/2019
Learning Implicitly Recurrent CNNs Through Parameter Sharing
We introduce a parameter sharing scheme, in which different layers of a ...
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04/05/2018
Regularizing Deep Networks by Modeling and Predicting Label Structure
We construct custom regularization functions for use in supervised train...
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12/13/2017
Self-Supervised Depth Learning for Urban Scene Understanding
As an agent moves through the world, the apparent motion of scene elemen...
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03/11/2017
Colorization as a Proxy Task for Visual Understanding
We investigate and improve self-supervision as a drop-in replacement for...
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11/23/2016
Multigrid Neural Architectures
We propose a multigrid extension of convolutional neural networks (CNNs)...
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05/24/2016
FractalNet: Ultra-Deep Neural Networks without Residuals
We introduce a design strategy for neural network macro-architecture bas...
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03/22/2016
Learning Representations for Automatic Colorization
We develop a fully automatic image colorization system. Our approach lev...
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12/09/2015
Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embedding
Spectral embedding provides a framework for solving perceptual organizat...
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12/08/2015
Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression
We introduce a new approach to intrinsic image decomposition, the task o...
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10/16/2014
Reconstructive Sparse Code Transfer for Contour Detection and Semantic Labeling
We frame the task of predicting a semantic labeling as a sparse reconstr...
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05/01/2014