Subhajit Chaudhury | DeepAI

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∙ 07/05/2023

Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning

Text-based reinforcement learning agents have predominantly been neural ...

0 Subhajit Chaudhury, et al. ∙

∙ 06/18/2023

MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types

With the growing interest in large language models, the need for evaluat...

6 Keerthiram Murugesan, et al. ∙

∙ 05/31/2023

Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency

We introduce Logical Offline Cycle Consistency Optimization (LOCCO), a s...

0 Maxwell Crouse, et al. ∙

∙ 05/07/2023

Laziness Is a Virtue When It Comes to Compositionality in Neural Semantic Parsing

Nearly all general-purpose neural semantic parsers generate logical form...

3 Maxwell Crouse, et al. ∙

∙ 10/23/2022

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach

Machine learning problems with multiple objective functions appear eithe...

0 Heshan Fernando, et al. ∙

∙ 10/21/2021

LOA: Logical Optimal Actions for Text-based Interaction Games

We present Logical Optimal Actions (LOA), an action decision architectur...

0 Daiki Kimura, et al. ∙

∙ 10/21/2021

Neuro-Symbolic Reinforcement Learning with First-Order Logic

Deep reinforcement learning (RL) methods often require many trials befor...

0 Daiki Kimura, et al. ∙

∙ 06/09/2021

Eye of the Beholder: Improved Relation Generalization for Text-based Reinforcement Learning Agents

Text-based games (TBGs) have become a popular proving ground for the dem...

4 Keerthiram Murugesan, et al. ∙

∙ 03/03/2021

Reinforcement Learning with External Knowledge by using Logical Neural Networks

Conventional deep reinforcement learning methods are sample-inefficient ...

0 Daiki Kimura, et al. ∙

∙ 12/03/2020

Image inpainting using frequency domain priors

In this paper, we present a novel image inpainting technique using frequ...

0 Hiya Roy, et al. ∙

∙ 10/26/2020

VisualHints: A Visual-Lingual Environment for Multimodal Reinforcement Learning

We present VisualHints, a novel environment for multimodal reinforcement...

8 Thomas Carta, et al. ∙

∙ 09/24/2020

Bootstrapped Q-learning with Context Relevant Observation Pruning to Generalize in Text-based Games

We show that Reinforcement Learning (RL) methods for solving Text-Based ...

0 Subhajit Chaudhury, et al. ∙

∙ 03/14/2020

Investigating Generalization in Neural Networks under Optimally Evolved Training Perturbations

In this paper, we study the generalization properties of neural networks...

0 Subhajit Chaudhury, et al. ∙

∙ 02/19/2020

Unsupervised Temporal Feature Aggregation for Event Detection in Unstructured Sports Videos

Image-based sports analytics enable automatic retrieval of key events in...

57 Subhajit Chaudhury, et al. ∙

∙ 04/14/2019

Lunar surface image restoration using U-net based deep neural networks

Image restoration is a technique that reconstructs a feasible estimate o...

0 Hiya Roy, et al. ∙

∙ 10/02/2018

Video Imitation GAN: Learning control policies by imitating raw videos using generative adversarial reward estimation

Natural imitation in humans usually consists of mimicking visual demonst...

0 Subhajit Chaudhury, et al. ∙

∙ 09/21/2018

Constrained Exploration and Recovery from Experience Shaping

We consider the problem of reinforcement learning under safety requireme...

0 Tu-Hoa Pham, et al. ∙

∙ 07/04/2018

Transfer Learning From Synthetic To Real Images Using Variational Autoencoders For Precise Position Detection

Capturing and labeling camera images in the real world is an expensive t...

0 Tadanobu Inoue, et al. ∙

∙ 06/22/2018

Focusing on What is Relevant: Time-Series Learning and Understanding using Attention

This paper is a contribution towards interpretability of the deep learni...

0 Phongtharin Vinayavekhin, et al. ∙

∙ 06/02/2018

Internal Model from Observations for Reward Shaping

Reinforcement learning methods require careful design involving a reward...

0 Daiki Kimura, et al. ∙

∙ 09/20/2017

Transfer learning from synthetic to real images using variational autoencoders for robotic applications

Robotic learning in simulation environments provides a faster, more scal...

0 Tadanobu Inoue, et al. ∙

∙ 07/04/2017

Conditional generation of multi-modal data using constrained embedding space mapping

We present a conditional generative model that maps low-dimensional embe...

0 Subhajit Chaudhury, et al. ∙

∙ 11/14/2016

Can fully convolutional networks perform well for general image restoration problems?

We present a fully convolutional network(FCN) based approach for color i...

0 Subhajit Chaudhury, et al. ∙

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