Search Results for author: Sandeep Kumar

Found 32 papers, 9 papers with code

A Unified Framework for Optimization-Based Graph Coarsening

no code implementations2 Oct 2022 Manoj Kumar, Anurag Sharma, Sandeep Kumar

In this paper, we introduce a novel optimization-based framework for graph dimensionality reduction.

Dimensionality Reduction Graph Learning

Enhancement to Training of Bidirectional GAN : An Approach to Demystify Tax Fraud

no code implementations16 Aug 2022 Priya Mehta, Sandeep Kumar, Ravi Kumar, Ch. Sobhan Babu

To validate the proposed approach, we train a BiGAN with the proposed training approach to detect taxpayers, who are manipulating their tax returns.

Outlier Detection

Robust Graph Neural Networks using Weighted Graph Laplacian

1 code implementation3 Aug 2022 Bharat Runwal, Vivek, Sandeep Kumar

For demonstration, the experiments are conducted with Graph convolutional neural network(GCNN) architecture, however, the proposed framework is easily amenable to any existing GNN architecture.

SMU: smooth activation function for deep networks using smoothing maximum technique

3 code implementations8 Nov 2021 Koushik Biswas, Sandeep Kumar, Shilpak Banerjee, Ashish Kumar Pandey

A good choice of activation function can have significant consequences in improving network performance.

SAU: Smooth activation function using convolution with approximate identities

no code implementations27 Sep 2021 Koushik Biswas, Sandeep Kumar, Shilpak Banerjee, Ashish Kumar Pandey

Well-known activation functions like ReLU or Leaky ReLU are non-differentiable at the origin.

Closed-loop targeted optogenetic stimulation of C. elegans populations

1 code implementation11 Sep 2021 Mochi Liu, Sandeep Kumar, Anuj K Sharma, Andrew M Leifer

The instrument addresses three technical challenges: it delivers targeted illumination to specified regions of the animal's body such as its head or tail; it automatically delivers stimuli triggered upon the animal's behavior; and it achieves high throughput by targeting many animals simultaneously.

ErfAct and Pserf: Non-monotonic Smooth Trainable Activation Functions

no code implementations9 Sep 2021 Koushik Biswas, Sandeep Kumar, Shilpak Banerjee, Ashish Kumar Pandey

An activation function is a crucial component of a neural network that introduces non-linearity in the network.

Tropical cyclone intensity estimations over the Indian ocean using Machine Learning

no code implementations7 Jul 2021 Koushik Biswas, Sandeep Kumar, Ashish Kumar Pandey

We use multi-class classification models for the categorical outcome variable, cyclone grade, and regression models for MSWS as it is a continuous variable.

BIG-bench Machine Learning Multi-class Classification

Intensity Prediction of Tropical Cyclones using Long Short-Term Memory Network

no code implementations7 Jul 2021 Koushik Biswas, Sandeep Kumar, Ashish Kumar Pandey

Therefore, the prediction of the intensity of tropical cyclones advance in time is of utmost importance.

Prediction of Landfall Intensity, Location, and Time of a Tropical Cyclone

1 code implementation30 Mar 2021 Sandeep Kumar, Koushik Biswas, Ashish Kumar Pandey

The model takes as input the best track data of cyclone consisting of its location, pressure, sea surface temperature, and intensity for certain hours (from 12 to 36 hours) anytime during the course of the cyclone as a time series and then provide predictions with high accuracy.

Time Series

Predicting Landfall's Location and Time of a Tropical Cyclone Using Reanalysis Data

1 code implementation30 Mar 2021 Sandeep Kumar, Koushik Biswas, Ashish Kumar Pandey

Landfall of a tropical cyclone is the event when it moves over the land after crossing the coast of the ocean.

Weather Forecasting

Static and Dynamical, Fractional Uncertainty Principles

no code implementations5 Mar 2021 Sandeep Kumar, Felipe Ponce-Vanegas, Luis Vega

We study the process of dispersion of low-regularity solutions to the Schr\"odinger equation using fractional weights (observables).

Analysis of PDEs 35J10, 35B99

EIS -- a family of activation functions combining Exponential, ISRU, and Softplus

no code implementations28 Sep 2020 Koushik Biswas, Sandeep Kumar, Shilpak Banerjee, Ashish Kumar Pandey

In recent years, several novel activation functions arising from these basic functions have been proposed, which have improved accuracy in some challenging datasets.

TanhSoft -- a family of activation functions combining Tanh and Softplus

no code implementations8 Sep 2020 Koushik Biswas, Sandeep Kumar, Shilpak Banerjee, Ashish Kumar Pandey

Deep learning at its core, contains functions that are composition of a linear transformation with a non-linear function known as activation function.

General Classification Image Classification

A Novel GDP Prediction Technique based on Transfer Learning using CO2 Emission Dataset

no code implementations2 May 2020 Sandeep Kumar, Pranab K. Muhuri

In the last 150 years, CO2 concentration in the atmosphere has increased from 280 parts per million to 400 parts per million.

Transfer Learning

Deep Bayesian Network for Visual Question Generation

no code implementations23 Jan 2020 Badri N. Patro, Vinod K. Kurmi, Sandeep Kumar, Vinay P. Namboodiri

This is a Bayesian framework and the results show a remarkable similarity to natural questions as validated by a human study.

Natural Questions Question Generation

Structured Graph Learning Via Laplacian Spectral Constraints

2 code implementations NeurIPS 2019 Sandeep Kumar, Jiaxi Ying, Jos'e Vin'icius de M. Cardoso, Daniel P. Palomar

Then we introduce a unified graph learning framework, lying at the integration of the spectral properties of the Laplacian matrix with Gaussian graphical modeling that is capable of learning structures of a large class of graph families.

Graph Learning

Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I

no code implementations21 Jul 2019 Sandeep Kumar, Ketan Rajawat, Daniel P. Palomar

Different from a number of existing approaches, however, the proposed framework is flexible enough to incorporate a class of non-convex objective functions, allow distributed operation with and without a fusion center, and include variance reduced methods as special cases.

A Unified Framework for Structured Graph Learning via Spectral Constraints

3 code implementations22 Apr 2019 Sandeep Kumar, Jiaxi Ying, José Vinícius de M. Cardoso, Daniel Palomar

Then we develop an optimization framework that leverages graph learning with specific structures via spectral constraints on graph matrices.

Graph Learning

Moonshots for aging

no code implementations13 Jan 2019 Sandeep Kumar, Timothy R. Peterson

As the global population ages, there is increased interest in living longer and improving one's quality of life in later years.

Philosophy

Live Detection of Face Using Machine Learning with Multi-feature Method

no code implementations27 Jul 2018 Sandeep Kumar, Sukhwinder Singh, Jagdish Kumar

This research proposed a new algorithm for automatic live FED using radial basis function; Haar discrete wavelet transform and Gray-level difference method is used for feature extraction and classification.

BIG-bench Machine Learning Face Detection +2

Learning Semantic Sentence Embeddings using Sequential Pair-wise Discriminator

2 code implementations COLING 2018 Badri N. Patro, Vinod K. Kurmi, Sandeep Kumar, Vinay P. Namboodiri

One way to ensure this is by adding constraints for true paraphrase embeddings to be close and unrelated paraphrase candidate sentence embeddings to be far.

Paraphrase Generation Sentence Embedding +2

Design and Implementation of Modified Fuzzy based CPU Scheduling Algorithm

no code implementations26 May 2017 Rajani Kumari, Vivek Kumar Sharma, Sandeep Kumar

Scheduling is a process which decides order of task from a set of multiple tasks that are ready to execute.

Stochastic Multidimensional Scaling

no code implementations21 Dec 2016 Ketan Rajawat, Sandeep Kumar

Multidimensional scaling (MDS) is a popular dimensionality reduction techniques that has been widely used for network visualization and cooperative localization.

Dimensionality Reduction Stochastic Optimization

Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach

no code implementations30 Nov 2016 Sandeep Kumar, Sindhu Padakandla, Chandrashekar L, Priyank Parihar, K Gopinath, Shalabh Bhatnagar

Our method, when tested on a 25 node Hadoop cluster shows 66\% decrease in execution time of Hadoop jobs on an average, when compared to the default configuration.

Memetic Search in Differential Evolution Algorithm

no code implementations1 Aug 2014 Sandeep Kumar, Vivek Kumar Sharma, Rajani Kumari

The proposed strategy is named as Memetic Search in Differential Evolution (MSDE).

Randomized Memetic Artificial Bee Colony Algorithm

no code implementations1 Aug 2014 Sandeep Kumar, Vivek Kumar Sharma, Rajani Kumari

In order to balance between diversification and intensification capability of the Memetic ABC, it is randomized the step size in Memetic ABC.

Improved Onlooker Bee Phase in Artificial Bee Colony Algorithm

no code implementations22 Jul 2014 Sandeep Kumar, Vivek Kumar Sharma, Rajani Kumari

Artificial Bee Colony (ABC) is a distinguished optimization strategy that can resolve nonlinear and multifaceted problems.

A Novel Hybrid Crossover based Artificial Bee Colony Algorithm for Optimization Problem

no code implementations21 Jul 2014 Sandeep Kumar, Vivek Kumar Sharma, Rajani Kumari

ABC has been proved its superiority over some other Nature Inspired Algorithms (NIA) when applied for both benchmark functions and real world problems.

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