Search Results for author: Gaurav Gupta

Found 24 papers, 11 papers with code

AS-IntroVAE: Adversarial Similarity Distance Makes Robust IntroVAE

no code implementations28 Jun 2022 Changjie Lu, Shen Zheng, ZiRui Wang, Omar Dib, Gaurav Gupta

However, due to the unavailability of an effective metric to evaluate the difference between the real and the fake images, the posterior collapse and the vanishing gradient problem still exist, reducing the fidelity of the synthesized images.

Image Generation

Functional Optimization Reinforcement Learning for Real-Time Bidding

no code implementations25 Jun 2022 Yining Lu, Changjie Lu, Naina Bandyopadhyay, Manoj Kumar, Gaurav Gupta

In order to evaluate the proposed RTB strategy's performance, we demonstrate the results on ten sequential simulated auction campaigns.

Multi-agent Reinforcement Learning reinforcement-learning

Secure Distributed/Federated Learning: Prediction-Privacy Trade-Off for Multi-Agent System

no code implementations24 Apr 2022 Mohamed Ridha Znaidi, Gaurav Gupta, Paul Bogdan

Decentralized learning is an efficient emerging paradigm for boosting the computing capability of multiple bounded computing agents.

Federated Learning Privacy Preserving

Unsupervised Domain Adaptation for Cardiac Segmentation: Towards Structure Mutual Information Maximization

1 code implementation20 Apr 2022 Changjie Lu, Shen Zheng, Gaurav Gupta

This paper introduces UDA-VAE++, an unsupervised domain adaptation framework for cardiac segmentation with a compact loss function lower bound.

Cardiac Segmentation Image Segmentation +3

SAPNet: Segmentation-Aware Progressive Network for Perceptual Contrastive Deraining

1 code implementation17 Nov 2021 Shen Zheng, Changjie Lu, Yuxiong Wu, Gaurav Gupta

To address this issue, in this paper, we present a segmentation-aware progressive network (SAPNet) based upon contrastive learning for single image deraining.

Contrastive Learning Image Restoration +4

Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancement

1 code implementation3 Oct 2021 Shen Zheng, Gaurav Gupta

Firstly, we design an enhancement factor extraction network using depthwise separable convolution for an efficient estimate of the pixel-wise light deficiency of an low-light image.

Low-Light Image Enhancement Unsupervised Semantic Segmentation +2

STORM: Sketch Toward Online Risk Minimization

no code implementations29 Sep 2021 Gaurav Gupta, Benjamin Coleman, John Chen, Anshumali Shrivastava

To this end, we propose STORM, an online sketching-based method for empirical risk minimization.

Classification

Non-Linear Operator Approximations for Initial Value Problems

no code implementations ICLR 2022 Gaurav Gupta, Xiongye Xiao, Radu Balan, Paul Bogdan

The Padé exponential operator uses a $\textit{recurrent structure with shared parameters}$ to model the non-linearity compared to recent neural operators that rely on using multiple linear operator layers in succession.

Multiwavelet-based Operator Learning for Differential Equations

1 code implementation NeurIPS 2021 Gaurav Gupta, Xiongye Xiao, Paul Bogdan

The solution of a partial differential equation can be obtained by computing the inverse operator map between the input and the solution space.

Operator learning

Non-Markovian Reinforcement Learning using Fractional Dynamics

no code implementations29 Jul 2021 Gaurav Gupta, Chenzhong Yin, Jyotirmoy V. Deshmukh, Paul Bogdan

Reinforcement learning (RL) is a technique to learn the control policy for an agent that interacts with a stochastic environment.

reinforcement-learning

IRLI: Iterative Re-partitioning for Learning to Index

no code implementations17 Mar 2021 Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J Smola

Neural models have transformed the fundamental information retrieval problem of mapping a query to a giant set of items.

Information Retrieval Multi-Label Classification

Noisy Batch Active Learning with Deterministic Annealing

1 code implementation27 Sep 2019 Gaurav Gupta, Anit Kumar Sahu, Wan-Yi Lin

We study the problem of training machine learning models incrementally with batches of samples annotated with noisy oracles.

Active Learning Denoising +1

Learning in Confusion: Batch Active Learning with Noisy Oracle

no code implementations25 Sep 2019 Gaurav Gupta, Anit Kumar Sahu, Wan-Yi Lin

We study the problem of training machine learning models incrementally using active learning with access to imperfect or noisy oracles.

Active Learning Denoising +1

Learning Information Propagation in the Dynamical Systems via Information Bottleneck Hierarchy

no code implementations ICLR 2019 Gaurav Gupta, Mohamed Ridha Znaidi, Paul Bogdan

Extracting relevant information, causally inferring and predicting the future states with high accuracy is a crucial task for modeling complex systems.

Causal Inference

Data-driven Perception of Neuron Point Process with Unknown Unknowns

1 code implementation2 Nov 2018 Ruochen Yang, Gaurav Gupta, Paul Bogdan

Previous research of neuron activity analysis is mainly limited with effects from the spiking history of target neuron and the interaction with other neurons in the system while ignoring the influence of unknown stimuli.

Activity Prediction Time Series

Learning Latent Fractional dynamics with Unknown Unknowns

1 code implementation2 Nov 2018 Gaurav Gupta, Sergio Pequito, Paul Bogdan

Despite significant effort in understanding complex systems (CS), we lack a theory for modeling, inference, analysis and efficient control of time-varying complex networks (TVCNs) in uncertain environments.

Approximate Submodular Functions and Performance Guarantees

no code implementations17 Jun 2018 Gaurav Gupta, Sergio Pequito, Paul Bogdan

Nonetheless, often we leverage the greedy algorithms used in submodular functions to determine a solution to the non-submodular functions.

Anonymizing k-Facial Attributes via Adversarial Perturbations

no code implementations23 May 2018 Saheb Chhabra, Richa Singh, Mayank Vatsa, Gaurav Gupta

A face image not only provides details about the identity of a subject but also reveals several attributes such as gender, race, sexual orientation, and age.

Dealing with Unknown Unknowns: Identification and Selection of Minimal Sensing for Fractional Dynamics with Unknown Inputs

1 code implementation10 Mar 2018 Gaurav Gupta, Sergio Pequito, Paul Bogdan

This paper focuses on analysis and design of time-varying complex networks having fractional order dynamics.

EEG

Passive Classification of Source Printer using Text-line-level Geometric Distortion Signatures from Scanned Images of Printed Documents

no code implementations20 Jun 2017 Hardik Jain, Gaurav Gupta, Sharad Joshi, Nitin Khanna

This paper proposes a set of features for characterizing text-line-level geometric distortions, referred as geometric distortion signatures and presents a novel system to use them for identification of the origin of a printed document.

General Classification

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