Posts by Collection

IR-IITBHU at TREC 2016 Open Search Track: Retrieving documents using Divergence From Randomness model in Terrier

Published in The Twenty-Fifth Text REtrieval Conference (TREC 2016) Proceedings. NIST Special Publication:SP 500-321, 2017

TREc 2016 Open Search Track

Recommended citation: M. Niyogi, S. Pal. (2017). "IR-IITBHU at TREC 2016 Open Search Track: Retrieving documents using Divergence From Randomness model in Terrier." The Twenty-Fifth Text REtrieval Conference (TREC 2016) Proceedings. NIST Special Publication:SP 500-321. https://trec.nist.gov/pubs/trec25/papers/IR-IITBHU-O.pdf

Business: Do you wanna sell more? Discovering Topics, Sentiments and Prediction of Ratings

Published in In Proceedings of the 7th International Conference on Computer and Communication Technology (ICCCT-2017). Association for Computing Machinery, New York, NY, USA, 133–138., 2017

Paper about topic modeling, sentiment analysis on Yelp Reviews

Recommended citation: Niyogi, M., Kumar Pal, A. (2019). "Business: Do you wanna sell more? Discovering Topics, Sentiments and Prediction of Ratings." In Proceedings of the 7th International Conference on Computer and Communication Technology (ICCCT-2017). Association for Computing Machinery, New York, NY, USA, 133–138. https://dl.acm.org/doi/10.1145/3154979.3154987

Learning Multilingual Embeddings for Cross-Lingual Information Retrieval in the Presence of Topically Aligned Corpora

Published in arXiv preprint arXiv:1804.04475v1, 2018

Cross-lingual Information Retrieval

Recommended citation: M. Niyogi, K. Ghosh, and A. Bhattacharya. (2018). "Learning Multilingual Embeddings for Cross-Lingual Information Retrieval in the Presence of Topically Aligned Corpora." arXiv preprint arXiv:1804.04475v1. https://arxiv.org/pdf/1804.04475.pdf

Discovering Conversational Topics and Emotions Associated with Demonetization Tweets in India

Published in In: Verma, N., Ghosh, A. (eds) Computational Intelligence: Theories, Applications and Future Directions - Volume I. Advances in Intelligent Systems and Computing, vol 798. Springer, Singapore, 2018

Paper about topic modeling, sentiment analysis on tweets related to Demonetization in India.

Recommended citation: Niyogi, M., Kumar Pal, A. (2019). "Discovering Conversational Topics and Emotions Associated with Demonetization Tweets in India." In: Verma, N., Ghosh, A. (eds) Computational Intelligence: Theories, Applications and Future Directions - Volume I. Advances in Intelligent Systems and Computing, vol 798. Springer, Singapore. https://link.springer.com/chapter/10.1007/978-981-13-1132-1_17

Neural Models for Source Code Synthesis and Completion

Published in IWR, Heidelberg University, Germany, 2021

LLM (BART, RoBERTa, Transformer, GPT2) to translate natural language to source code snippet (NL2Code) and code completion system.

Recommended citation: Mitodru Niyogi. (2021). "Neural Models for Source Code Synthesis and Completion." IWR, Heidelberg University, Germany. https://drive.google.com/file/d/1M3gXVON_-9NA401fOxY_mn30xVFuiPXT/view

Artist identification and generating new paintings using DC-GAN

Published: August 05, 2019

In this Poster Session, we presented our Deep Vision course project on image classification and image generation based on style of artist using DC-GAN architecture.

Special Topics in Continuous Optimization and Optimal Control: Local and Global convergence of Newton methods

Published: December 07, 2019

In this seminar talk, we discussed the local and global convergence of Newton Methods topics which are under as follows:

ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks

Published: January 15, 2020

At Vision and Language seminar, I presented the following paper and discussed its pros and cons!

Review of Faithful to the Original: Fact Aware Neural Abstractive Summarization: Ziqiang et al.

Published: January 22, 2020

At Neural Text Summarization seminar, I presented the following paper and discussed its pros and cons!

Review of Deep Recurrent Neural Networks for Prostate Cancer Detection: Analysis of Temporal Enhanced Ultrasound (Shekoofeh Aziz et al.)

Published: June 25, 2020

At BioMedical Image Analysis Seminar, I presented the following paper and discussed its pros and cons!

Neural Code Synthesis and Completion

Published: August 25, 2021

In my MS thesis, I presented my work on Neural Code generation from natural language and Neural code completion.

Paper Review: Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

Published: October 03, 2022

In this paper review, I reviewed one of the classical papers in NLP Socher et al., 2013

Research presentation at UKP Lab, TU Darmstadt

Published: November 21, 2022

In this research seminar, I participated to present my past research on neural generative code generation Mitodru Niyogi. (2021) and cross-lingual information retrieval for low-resource Indian languages Niyogi et al., 2018

Tutorial on Feature Importance

Published: June 23, 2023

In this tutorial, I discussed various feature importance methods for regression/classification setting as how to find important input features which drive the target feature. I also discussed the advantages, and disadvantages of these methods. A regression problem has been taken into consideration to determine the important factors which drive the regression target.