Search Results for author: Jaideep Srivastava

Found 16 papers, 4 papers with code

MOOCRep: A Unified Pre-trained Embedding of MOOC Entities

1 code implementation12 Jul 2021 Shalini Pandey, Jaideep Srivastava

Many machine learning models have been built to tackle information overload issues on Massive Open Online Courses (MOOC) platforms.

Language Modelling Representation Learning

Assessing Individual and Community Vulnerability to Fake News in Social Networks

no code implementations4 Feb 2021 Bhavtosh Rath, Wei Gao, Jaideep Srivastava

In this paper we base our idea on Computational Trust in social networks to propose a novel Community Health Assessment model against fake news.

Community Detection Social and Information Networks

An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset

no code implementations16 Jan 2021 Shalini Pandey, George Karypis, Jaideep Srivastava

Recent release of large-scale student performance dataset \cite{choi2019ednet} motivates the analysis of performance of deep learning approaches that have been proposed to solve KT.

Knowledge Tracing

Learning Student Interest Trajectory for MOOCThread Recommendation

no code implementations10 Jan 2021 Shalini Pandey, Andrew Lan, George Karypis, Jaideep Srivastava

The projection operation learns to estimate future embedding of students and threads.

RKT : Relation-Aware Self-Attention for Knowledge Tracing

1 code implementation28 Aug 2020 Shalini Pandey, Jaideep Srivastava

The aim of KT is to model student's knowledge level based on their answers to a sequence of exercises referred as interactions.

Knowledge Tracing

A Structured Learning Approach with Neural Conditional Random Fields for Sleep Staging

no code implementations23 Jul 2018 Karan Aggarwal, Swaraj Khadanga, Shafiq R. Joty, Louis Kazaglis, Jaideep Srivastava

We propose an end-to-end framework that uses a combination of deep convolution and recurrent neural networks to extract high-level features from raw flow signal with a structured output layer based on a conditional random field to model the temporal transition structure of the sleep stages.

Hyperedge2vec: Distributed Representations for Hyperedges

no code implementations ICLR 2018 Ankit Sharma, Shafiq Joty, Himanshu Kharkwal, Jaideep Srivastava

We present a number of interesting baselines, some of which adapt existing node-level embedding models to the hyperedge-level, as well as sequence based language techniques which are adapted for set structured hypergraph topology.

Probabilistic Deep Learning

Predictive Overlapping Co-Clustering

no code implementations8 Mar 2014 Chandrima Sarkar, Jaideep Srivastava

In this paper, we present the novel idea of Predictive Overlapping Co-Clustering (POCC) as an optimization problem for a more effective and improved predictive analysis.

Community Detection Recommendation Systems

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