
WarpRefine Propagation: SemiSupervised Autolabeling via Cycleconsistency
Deep learning models for semantic segmentation rely on expensive, large...
read it

UncertaintyAware SelfSupervised TargetMass Grasping of Granular Foods
Food packing industry workers typically pick a target amount of food by ...
read it

Meta Learning as Bayes Risk Minimization
MetaLearning is a family of methods that use a set of interrelated task...
read it

MANGA: Method Agnostic Neuralpolicy Generalization and Adaptation
In this paper we target the problem of transferring policies across mult...
read it

Reconnaissance and Planning algorithm for constrained MDP
Practical reinforcement learning problems are often formulated as constr...
read it

Einconv: Exploring Unexplored Tensor Decompositions for Convolutional Neural Networks
Tensor decomposition methods are one of the primary approaches for model...
read it

Robustness to Adversarial Perturbations in Learning from Incomplete Data
What is the role of unlabeled data in an inference problem, when the pre...
read it

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...
read it

DQNTAMER: HumanintheLoop Reinforcement Learning with Intractable Feedback
Exploration has been one of the greatest challenges in reinforcement lea...
read it

BayesGrad: Explaining Predictions of Graph Convolutional Networks
Recent advances in graph convolutional networks have significantly impro...
read it

Neural Multiscale Image Compression
This study presents a new lossy image compression method that utilizes t...
read it

Clipped Action Policy Gradient
Many continuous control tasks have bounded action spaces and clip outof...
read it

Semisupervised learning of hierarchical representations of molecules using neural message passing
With the rapid increase of compound databases available in medicinal and...
read it

Neural Sequence Model Training via αdivergence Minimization
We propose a new neural sequence model training method in which the obje...
read it

Virtual Adversarial Training: a Regularization Method for Supervised and Semisupervised Learning
We propose a new regularization method based on virtual adversarial loss...
read it

Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias
A common strategy for sparse linear regression is to introduce regulariz...
read it

Distributional Smoothing with Virtual Adversarial Training
We propose local distributional smoothness (LDS), a new notion of smooth...
read it

Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood
Factorized information criterion (FIC) is a recently developed approxima...
read it

A Bayesian encourages dropout
Dropout is one of the key techniques to prevent the learning from overfi...
read it
Shinichi Maeda
is this you? claim profile