Sanjiv Das

According to our database, Sanjiv Das authored at least 10 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Project Life Cycles in Open-Source Software.

Sanjiv Das, Andrii Ieroshenko, Piyush Jain, David Qiu, Michael Chin, Brian Granger

CoRR, May, 2026

Yield Curve Forecasting using Machine Learning and Econometrics: A Comparative Analysis.

Aman Singh, Tokunbo Ogunfunmi, Sanjiv Das

CoRR, May, 2026

2024

PPLqa: An Unsupervised Information-Theoretic Quality Metric for Comparing Generative Large Language Models.

Gerald Friedland, Xin Huang, Yueying Cui, Vishaal Kapoor, Ashish Khetan, Sanjiv Das

CoRR, 2024

2023

Utility-Preserving Privacy-Enabled Speech Embeddings for Emotion Detection.

Chandrashekhar Lavania, Sanjiv Das, Xin Huang, Kyu J. Han

Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

A System for Analyzing Human Capability at Scale Using AI.

Daniel Zhu, Dave Ulrich, Sanjiv Das, Norm Smallwood

Proceedings of the Intelligent Systems and Applications, 2023

2022

Diverse Counterfactual Explanations for Anomaly Detection in Time Series.

Déborah Sulem, Michele Donini, Muhammad Bilal Zafar, Francois-Xavier Aubet, Jan Gasthaus, Tim Januschowski, Sanjiv Das, Krishnaram Kenthapadi, Cédric Archambeau

CoRR, 2022

Intelligent Probabilistic Forecasts of VIX and its Volatility using Machine Learning Methods.

Aerambamoorthy Thavaneswaran, You Liang, Sanjiv Das, Ruppa K. Thulasiram, Janakumar Bhanushali

Proceedings of the IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, 2022

2021

More Than Words: Towards Better Quality Interpretations of Text Classifiers.

Muhammad Bilal Zafar, Philipp Schmidt, Michele Donini, Cédric Archambeau, Felix Biessmann, Sanjiv Ranjan Das, Krishnaram Kenthapadi

CoRR, 2021

Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud.

Michaela Hardt, Xiaoguang Chen, Xiaoyi Cheng, Michele Donini, Jason Gelman, Satish Gollaprolu, John He, Pedro Larroy, Xinyu Liu, Nick McCarthy, Ashish Rathi, Scott Rees, Amaresh Ankit Siva, ErhYuan Tsai, Keerthan Vasist, Pinar Yilmaz, Muhammad Bilal Zafar, Sanjiv Das, Kevin Haas, Tyler Hill, Krishnaram Kenthapadi

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

On the Lack of Robust Interpretability of Neural Text Classifiers.

Muhammad Bilal Zafar, Michele Donini, Dylan Slack, Cédric Archambeau, Sanjiv Das, Krishnaram Kenthapadi

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021