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11/15/2021
Contrastive Representation Learning with Trainable Augmentation Channel
In contrastive representation learning, data representation is trained s...
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08/04/2020
Out-of-Distribution Generalization with Maximal Invariant Predictor
Out-of-Distribution (OOD) generalization problem is a problem of seeking...
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07/21/2020
Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective
Learning controllable and generalizable representation of multivariate d...
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06/02/2020
Meta Learning as Bayes Risk Minimization
Meta-Learning is a family of methods that use a set of interrelated task...
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09/20/2019
Reconnaissance and Planning algorithm for constrained MDP
Practical reinforcement learning problems are often formulated as constr...
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07/25/2019
Optuna: A Next-generation Hyperparameter Optimization Framework
The purpose of this study is to introduce new design-criteria for next-g...
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05/28/2019
A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation
Recomputation algorithms collectively refer to a family of methods that ...
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05/24/2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data
What is the role of unlabeled data in an inference problem, when the pre...
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02/08/2019
A Differentiable Gaussian-like Distribution on Hyperbolic Space for Gradient-Based Learning
Hyperbolic space is a geometry that is known to be well-suited for repre...
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02/04/2019
Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks
Recently, Graph Neural Networks (GNNs) are trending in the machine learn...
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11/26/2018
Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration
We present a novel CNN-based image editing method that allows the user t...
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02/16/2018
Spectral Normalization for Generative Adversarial Networks
One of the challenges in the study of generative adversarial networks is...
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02/15/2018
cGANs with Projection Discriminator
We propose a novel, projection based way to incorporate the conditional ...
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04/13/2017
Virtual Adversarial Training: a Regularization Method for Supervised and Semi-supervised Learning
We propose a new regularization method based on virtual adversarial loss...
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07/02/2015
Distributional Smoothing with Virtual Adversarial Training
We propose local distributional smoothness (LDS), a new notion of smooth...
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01/31/2015
Deep learning of fMRI big data: a novel approach to subject-transfer decoding
As a technology to read brain states from measurable brain activities, b...
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12/21/2014