Indian Institute Of Technology, Madras

∙ Chennai , India ∙ 0 followers

23362 Indian Institute of Technology Madras is a public engineering institute located in Chennai, Tamil Nadu.

SEERL: Sample Efficient Ensemble Reinforcement Learning

Ensemble learning is a very prevalent method employed in machine learnin...
01/15/2020 ∙ by Rohan Saphal, et al. ∙ 43 ∙ share

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Hypergraph Clustering: A Modularity Maximization Approach

Clustering on hypergraphs has been garnering increased attention with po...
12/28/2018 ∙ by Tarun Kumar, et al. ∙ 28 ∙ share

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Optimal Resampling for Learning Small Models

Models often need to be constrained to a certain size for them to be con...
05/04/2019 ∙ by Abhishek Ghose, et al. ∙ 26 ∙ share

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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...
08/25/2019 ∙ by Balamurali Murugesan, et al. ∙ 24 ∙ share

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Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning

In the domain of algorithmic music composition, machine learning-driven ...
02/05/2019 ∙ by Harish Kumar, et al. ∙ 18 ∙ share

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

Histopathology tissue analysis is considered the gold standard in cancer...
01/01/2020 ∙ by Mahendra Khened, et al. ∙ 14 ∙ share

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

Magnetic Resonance (MR) Imaging and Computed Tomography (CT) are the pri...
06/05/2020 ∙ by Vismay Agrawal, et al. ∙ 14 ∙ share

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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...
07/08/2019 ∙ by Vikas Dwivedi, et al. ∙ 13 ∙ share

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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...
12/26/2018 ∙ by Deepak Mittal, et al. ∙ 12 ∙ share

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Online Lifelong Generalized Zero-Shot Learning

Methods proposed in the literature for zero-shot learning (ZSL) are typi...
03/19/2021 ∙ by Chandan Gautam, et al. ∙ 12 ∙ share

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MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning

Shaping in humans and animals has been shown to be a powerful tool for l...
05/17/2019 ∙ by Manan Tomar, et al. ∙ 11 ∙ share

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

Light Field (LF) offers unique advantages such as post-capture refocusin...
03/05/2020 ∙ by Mohit Lamba, et al. ∙ 11 ∙ share

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An Active Learning Framework for Efficient Robust Policy Search

Robust Policy Search is the problem of learning policies that do not deg...
01/01/2019 ∙ by Sai Kiran Narayanaswami, et al. ∙ 10 ∙ share

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A Systematic Evaluation of Object Detection Networks for Scientific Plots

Are existing object detection methods adequate for detecting text and vi...
07/05/2020 ∙ by Pritha Ganguly, et al. ∙ 10 ∙ share

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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...
12/26/2018 ∙ by Anil Kumar Vadathya, et al. ∙ 8 ∙ share

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ExTra: Transfer-guided Exploration

In this work we present a novel approach for transfer-guided exploration...
06/27/2019 ∙ by Anirban Santara, et al. ∙ 8 ∙ share

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

Certain facial parts are salient (unique) in appearance, which substanti...
02/19/2020 ∙ by Samik Banerjee, et al. ∙ 8 ∙ share

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Learning Interpretable Models Using an Oracle

As Machine Learning (ML) becomes pervasive in various real world systems...
06/17/2019 ∙ by Abhishek Ghose, et al. ∙ 7 ∙ share

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Successor Options: An Option Discovery Framework for Reinforcement Learning

The options framework in reinforcement learning models the notion of a s...
05/14/2019 ∙ by Rahul Ramesh, et al. ∙ 6 ∙ share

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

Option discovery and skill acquisition frameworks are integral to the fu...
09/09/2019 ∙ by Arjun Manoharan, et al. ∙ 6 ∙ share

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Robust Super-Resolution of Real Faces using Smooth Features

Real low-resolution (LR) face images contain degradations which are too ...
11/04/2020 ∙ by Saurabh Goswami, et al. ∙ 2 ∙ share

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Correlational Neural Networks

Common Representation Learning (CRL), wherein different descriptions (or...
04/27/2015 ∙ by Sarath Chandar, et al. ∙ 0 ∙ share

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Generalized Zero-Shot Learning via Synthesized Examples

We present a generative framework for generalized zero-shot learning whe...
12/11/2017 ∙ by Gundeep Arora, et al. ∙ 0 ∙ share

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Extracting Ontological Knowledge from Textual Descriptions

Authoring of OWL-DL ontologies is intellectually challenging and to make...
09/25/2017 ∙ by Kevin Alex Mathews, et al. ∙ 0 ∙ share

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DyVEDeep: Dynamic Variable Effort Deep Neural Networks

Deep Neural Networks (DNNs) have advanced the state-of-the-art in a vari...
04/04/2017 ∙ by Sanjay Ganapathy, et al. ∙ 0 ∙ share

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Shared Learning : Enhancing Reinforcement in Q-Ensembles

Deep Reinforcement Learning has been able to achieve amazing successes i...
09/14/2017 ∙ by Rakesh R Menon, et al. ∙ 0 ∙ share

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

Reinforcement Learning algorithms can learn complex behavioral patterns ...
02/20/2017 ∙ by Sahil Sharma, et al. ∙ 0 ∙ share

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Difficulty-level Modeling of Ontology-based Factual Questions

Semantics based knowledge representations such as ontologies are found t...
09/03/2017 ∙ by Vinu E. V, et al. ∙ 0 ∙ share

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Dynamic Frame skip Deep Q Network

Deep Reinforcement Learning methods have achieved state of the art perfo...
05/17/2016 ∙ by Aravind S. Lakshminarayanan, et al. ∙ 0 ∙ share

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

Reinforcement Learning (RL) can model complex behavior policies for goal...
05/21/2017 ∙ by Sahil Sharma, et al. ∙ 0 ∙ share

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

Wireless systems perform rate adaptation to transmit at highest possible...
08/03/2017 ∙ by Saishankar Katri Pulliyakode, et al. ∙ 0 ∙ share

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Taming Non-stationary Bandits: A Bayesian Approach

We consider the multi armed bandit problem in non-stationary environment...
07/31/2017 ∙ by Vishnu Raj, et al. ∙ 0 ∙ share

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Signal and Noise Statistics Oblivious Sparse Reconstruction using OMP/OLS

Orthogonal matching pursuit (OMP) and orthogonal least squares (OLS) are...
07/27/2017 ∙ by Sreejith Kallummil, et al. ∙ 0 ∙ share

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Exploration for Multi-task Reinforcement Learning with Deep Generative Models

Exploration in multi-task reinforcement learning is critical in training...
11/29/2016 ∙ by Sai Praveen Bangaru, et al. ∙ 0 ∙ share

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Ontology Verbalization using Semantic-Refinement

We propose a rule-based technique to generate redundancy-free NL descrip...
10/31/2016 ∙ by Vinu E. V, et al. ∙ 0 ∙ share

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Tuning Free Orthogonal Matching Pursuit

Orthogonal matching pursuit (OMP) is a widely used compressive sensing (...
03/15/2017 ∙ by Sreejith Kallummil, et al. ∙ 0 ∙ share

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Domain Adaptation with Soft-margin multiple feature-kernel learning beats Deep Learning for surveillance face recognition

Face recognition (FR) is the most preferred mode for biometric-based sur...
10/05/2016 ∙ by Samik Banerjee, et al. ∙ 0 ∙ share

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EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

Sample complexity and safety are major challenges when learning policies...
10/05/2016 ∙ by Aravind Rajeswaran, et al. ∙ 0 ∙ share

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High SNR Consistent Compressive Sensing

High signal to noise ratio (SNR) consistency of model selection criteria...
03/10/2017 ∙ by Sreejith Kallummil, et al. ∙ 0 ∙ share

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Modeling of Item-Difficulty for Ontology-based MCQs

Multiple choice questions (MCQs) that can be generated from a domain ont...
07/04/2016 ∙ by Vinu E. V, et al. ∙ 0 ∙ share

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Enriching Linked Datasets with New Object Properties

Although several RDF knowledge bases are available through the LOD initi...
06/24/2016 ∙ by Subhashree S, et al. ∙ 0 ∙ share

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Learning and Tuning Meta-heuristics in Plan Space Planning

In recent years, the planning community has observed that techniques for...
01/27/2016 ∙ by Shashank Shekhar, et al. ∙ 0 ∙ share

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Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain

Transferring knowledge from prior source tasks in solving a new target t...
10/10/2015 ∙ by Janarthanan Rajendran, et al. ∙ 0 ∙ share

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Compressive Image Recovery Using Recurrent Generative Model

Reconstruction of signals from compressively sensed measurements is an i...
12/13/2016 ∙ by Akshat Dave, et al. ∙ 0 ∙ share

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Collaborative Learning of Stochastic Bandits over a Social Network

We consider a collaborative online learning paradigm, wherein a group of...
02/29/2016 ∙ by Ravi Kumar Kolla, et al. ∙ 0 ∙ share

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Bi-modal First Impressions Recognition using Temporally Ordered Deep Audio and Stochastic Visual Features

We propose a novel approach for First Impressions Recognition in terms o...
10/31/2016 ∙ by Arulkumar Subramaniam, et al. ∙ 0 ∙ share

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A Novel Approach for Phase Identification in Smart Grids Using Graph Theory and Principal Component Analysis

Consumers with low demand, like households, are generally supplied singl...
11/19/2015 ∙ by P Satya Jayadev, et al. ∙ 0 ∙ share

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Monotonous (Semi-)Nonnegative Matrix Factorization

Nonnegative matrix factorization (NMF) factorizes a non-negative matrix ...
05/01/2015 ∙ by Nirav Bhatt, et al. ∙ 0 ∙ share

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Adaptive Locally Affine-Invariant Shape Matching

Matching deformable objects using their shapes is an important problem i...
04/25/2015 ∙ by Smit Marvaniya, et al. ∙ 0 ∙ share

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Mixture of Parts Revisited: Expressive Part Interactions for Pose Estimation

Part-based models with restrictive tree-structured interactions for the ...
12/21/2014 ∙ by Anoop Katti, et al. ∙ 0 ∙ share

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Indian Institute Of Technology, Madras

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