Indian Institute Of Technology, Madras

research

∙ 01/15/2020

SEERL: Sample Efficient Ensemble Reinforcement Learning

Ensemble learning is a very prevalent method employed in machine learnin...

Rohan Saphal, et al. ∙

research

∙ 12/28/2018

Hypergraph Clustering: A Modularity Maximization Approach

Clustering on hypergraphs has been garnering increased attention with po...

Tarun Kumar, et al. ∙

research

∙ 05/04/2019

Optimal Resampling for Learning Small Models

Models often need to be constrained to a certain size for them to be con...

Abhishek Ghose, et al. ∙

research

∙ 08/25/2019

Recon-GLGAN: A Global-Local context based Generative Adversarial Network for MRI Reconstruction

Magnetic resonance imaging (MRI) is one of the best medical imaging moda...

Balamurali Murugesan, et al. ∙

research

∙ 10/28/2021

How to boost autoencoders?

Autoencoders are a category of neural networks with applications in nume...

Sai Krishna, et al. ∙

research

∙ 02/05/2019

Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning

In the domain of algorithmic music composition, machine learning-driven ...

Harish Kumar, et al. ∙

research

∙ 01/01/2020

A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and Analysis

Histopathology tissue analysis is considered the gold standard in cancer...

Mahendra Khened, et al. ∙

research

∙ 06/05/2020

Structurally aware bidirectional unpaired image to image translation between CT and MR

Magnetic Resonance (MR) Imaging and Computed Tomography (CT) are the pri...

Vismay Agrawal, et al. ∙

research

∙ 04/29/2022

Evolutionary Approach to Security Games with Signaling

Green Security Games have become a popular way to model scenarios involv...

Adam Żychowski, et al. ∙

research

∙ 07/08/2019

Physics Informed Extreme Learning Machine (PIELM) -- A rapid method for the numerical solution of partial differential equations

There has been rapid progress recently on the application of deep networ...

Vikas Dwivedi, et al. ∙

research

∙ 10/15/2021

Dynamic probabilistic logic models for effective abstractions in RL

State abstraction enables sample-efficient learning and better task tran...

Harsha Kokel, et al. ∙

research

∙ 12/26/2018

Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning

Recently there has been a lot of work on pruning filters from deep convo...

Deepak Mittal, et al. ∙

research

∙ 03/19/2021

Online Lifelong Generalized Zero-Shot Learning

Methods proposed in the literature for zero-shot learning (ZSL) are typi...

Chandan Gautam, et al. ∙

research

∙ 05/17/2019

MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning

Shaping in humans and animals has been shown to be a powerful tool for l...

Manan Tomar, et al. ∙

research

∙ 03/05/2020

Harnessing Multi-View Perspective of Light Fields for Low-Light Imaging

Light Field (LF) offers unique advantages such as post-capture refocusin...

Mohit Lamba, et al. ∙

research

∙ 01/01/2019

An Active Learning Framework for Efficient Robust Policy Search

Robust Policy Search is the problem of learning policies that do not deg...

Sai Kiran Narayanaswami, et al. ∙

research

∙ 07/05/2020

A Systematic Evaluation of Object Detection Networks for Scientific Plots

Are existing object detection methods adequate for detecting text and vi...

Pritha Ganguly, et al. ∙

research

∙ 10/05/2021

Semi-Supervised Deep Learning for Multiplex Networks

Multiplex networks are complex graph structures in which a set of entiti...

Anasua Mitra, et al. ∙

research

∙ 12/26/2018

A Unified Learning Based Framework for Light Field Reconstruction from Coded Projections

Light field presents a rich way to represent the 3D world by capturing t...

Anil Kumar Vadathya, et al. ∙

research

∙ 06/27/2019

ExTra: Transfer-guided Exploration

In this work we present a novel approach for transfer-guided exploration...

Anirban Santara, et al. ∙

research

∙ 02/19/2020

SD-GAN: Structural and Denoising GAN reveals facial parts under occlusion

Certain facial parts are salient (unique) in appearance, which substanti...

Samik Banerjee, et al. ∙

research

∙ 09/25/2021

Distributed Online Optimization with Byzantine Adversarial Agents

We study the problem of non-constrained, discrete-time, online distribut...

Sourav Sahoo, et al. ∙

research

∙ 06/17/2019

Learning Interpretable Models Using an Oracle

As Machine Learning (ML) becomes pervasive in various real world systems...

Abhishek Ghose, et al. ∙

research

∙ 05/14/2019

Successor Options: An Option Discovery Framework for Reinforcement Learning

The options framework in reinforcement learning models the notion of a s...

Rahul Ramesh, et al. ∙

research

∙ 09/09/2019

Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning

Option discovery and skill acquisition frameworks are integral to the fu...

Arjun Manoharan, et al. ∙

research

∙ 09/13/2021

Perturbation CheckLists for Evaluating NLG Evaluation Metrics

Natural Language Generation (NLG) evaluation is a multifaceted task requ...

Ananya B. Sai, et al. ∙

research

∙ 10/12/2021

OpenHands: Making Sign Language Recognition Accessible with Pose-based Pretrained Models across Languages

AI technologies for Natural Languages have made tremendous progress rece...

Prem Selvaraj, et al. ∙

research

∙ 10/15/2021

k – Online Policies and Fundamental Limits

This paper introduces and studies the k problem – a generalization of th...

Samrat Mukhopadhyay, et al. ∙

research

∙ 12/14/2021

Mitigating Channel-wise Noise for Single Image Super Resolution

In practice, images can contain different amounts of noise for different...

Srimanta Mandal, et al. ∙

research

∙ 01/28/2022

Unfolding a blurred image

We present a solution for the goal of extracting a video from a single m...

Kuldeep Purohit, et al. ∙

research

∙ 01/27/2022

Non-linear Motion Estimation for Video Frame Interpolation using Space-time Convolutions

Video frame interpolation aims to synthesize one or multiple frames betw...

Saikat Dutta, et al. ∙

research

∙ 03/23/2022

Input-specific Attention Subnetworks for Adversarial Detection

Self-attention heads are characteristic of Transformer models and have b...

Emil Biju, et al. ∙

research

∙ 11/06/2021

Towards Building ASR Systems for the Next Billion Users

Recent methods in speech and language technology pretrain very LARGE mod...

Tahir Javed, et al. ∙

research

∙ 11/23/2021

IR Motion Deblurring

Camera gimbal systems are important in various air or water borne system...

Nisha Varghese, et al. ∙

research

∙ 11/04/2020

Robust Super-Resolution of Real Faces using Smooth Features

Real low-resolution (LR) face images contain degradations which are too ...

Saurabh Goswami, et al. ∙

research

∙ 08/27/2021

A Novel Hierarchical Light Field Coding Scheme Based on Hybrid Stacked Multiplicative Layers and Fourier Disparity Layers for Glasses-Free 3D Displays

This paper presents a novel hierarchical coding scheme for light fields ...

Joshitha Ravishankar, et al. ∙

research

∙ 04/27/2015

Correlational Neural Networks

Common Representation Learning (CRL), wherein different descriptions (or...

Sarath Chandar, et al. ∙

research

∙ 12/11/2017

Generalized Zero-Shot Learning via Synthesized Examples

We present a generative framework for generalized zero-shot learning whe...

Gundeep Arora, et al. ∙

research

∙ 09/25/2017

Extracting Ontological Knowledge from Textual Descriptions

Authoring of OWL-DL ontologies is intellectually challenging and to make...

Kevin Alex Mathews, et al. ∙

research

∙ 04/04/2017

DyVEDeep: Dynamic Variable Effort Deep Neural Networks

Deep Neural Networks (DNNs) have advanced the state-of-the-art in a vari...

Sanjay Ganapathy, et al. ∙

research

∙ 09/14/2017

Shared Learning : Enhancing Reinforcement in Q-Ensembles

Deep Reinforcement Learning has been able to achieve amazing successes i...

Rakesh R Menon, et al. ∙

research

∙ 02/20/2017

Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning

Reinforcement Learning algorithms can learn complex behavioral patterns ...

Sahil Sharma, et al. ∙

research

∙ 09/03/2017

Difficulty-level Modeling of Ontology-based Factual Questions

Semantics based knowledge representations such as ontologies are found t...

Vinu E. V, et al. ∙

research

∙ 05/17/2016

Dynamic Frame skip Deep Q Network

Deep Reinforcement Learning methods have achieved state of the art perfo...

Aravind S. Lakshminarayanan, et al. ∙

research

∙ 05/21/2017

Learning to Mix n-Step Returns: Generalizing lambda-Returns for Deep Reinforcement Learning

Reinforcement Learning (RL) can model complex behavior policies for goal...

Sahil Sharma, et al. ∙

research

∙ 08/03/2017

Reinforcement learning techniques for Outer Loop Link Adaptation in 4G/5G systems

Wireless systems perform rate adaptation to transmit at highest possible...

Saishankar Katri Pulliyakode, et al. ∙

research

∙ 07/31/2017

Taming Non-stationary Bandits: A Bayesian Approach

We consider the multi armed bandit problem in non-stationary environment...

Vishnu Raj, et al. ∙

research

∙ 07/27/2017

Signal and Noise Statistics Oblivious Sparse Reconstruction using OMP/OLS

Orthogonal matching pursuit (OMP) and orthogonal least squares (OLS) are...

Sreejith Kallummil, et al. ∙

research

∙ 11/29/2016

Exploration for Multi-task Reinforcement Learning with Deep Generative Models

Exploration in multi-task reinforcement learning is critical in training...

Sai Praveen Bangaru, et al. ∙

research

∙ 10/31/2016

Ontology Verbalization using Semantic-Refinement

We propose a rule-based technique to generate redundancy-free NL descrip...

Vinu E. V, et al. ∙

Indian Institute Of Technology, Madras

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