Kamalika Das

According to our database, Kamalika Das authored at least 45 papers between 2006 and 2024.

Collaborative distances:

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

2024

Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation.

Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Kumar Sricharan, Murat Kantarcioglu, Bradley A. Malin

CoRR, 2024

PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models.

Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan

CoRR, 2024

DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models.

Wendi Cui, Jiaxin Zhang, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan

CoRR, 2024

DECDM: Document Enhancement using Cycle-Consistent Diffusion Models.

Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification.

Magesh Rajasekaran, Md Saiful Islam Sajol, Frej Berglind, Supratik Mukhopadhyay, Kamalika Das

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models.

Jiaxin Zhang, Wendi Cui, Yiran Huang, Kamalika Das, Kumar Sricharan

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation.

Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Kumar Sricharan, Murat Kantarcioglu, Bradley Malin

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models.

Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods.

Jiaxin Zhang, Kamalika Das, Kumar Sricharan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Customizing Language Model Responses with Contrastive In-Context Learning.

Xiang Gao, Kamalika Das

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

SAC³: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency.

Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan

CoRR, 2023

Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision.

Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SAC³: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency.

Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

XOOD: Extreme Value Based Out-Of-Distribution Detection For Image Classification.

Frej Berglind, Haron Temam, Supratik Mukhopadhyay, Kamalika Das, Md Saiful Islam Sajol, Kumar Sricharan, Kumar Kallurupalli

CoRR, 2022

2020

Learning Instrument Invariant Characteristics for Generating High-resolution Global Coral Reef Maps.

Ata Akbari Asanjan, Kamalika Das, Alan S. Li, Ved Chirayath, Juan Torres-Perez, Soroosh Sorooshian

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2018

CADDeLaG: Framework for distributed anomaly detection in large dense graph sequences.

Aniruddha Basak, Kamalika Das, Ole J. Mengshoel

CoRR, 2018

Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis.

Anuradha Kodali, Marcin Szubert, Kamalika Das, Sangram Ganguly, Joshua Clifford Bongard

Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

2017

ASK-the-Expert: Active Learning Based Knowledge Discovery Using the Expert.

Kamalika Das, Ilya Avrekh, Bryan L. Matthews, Manali Sharma, Nikunj C. Oza

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Semantic Forward Propagation for Symbolic Regression.

Marcin Szubert, Anuradha Kodali, Sangram Ganguly, Kamalika Das, Josh C. Bongard

Proceedings of the Parallel Problem Solving from Nature - PPSN XIV, 2016

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation.

Manali Sharma, Kamalika Das, Mustafa Bilgic, Bryan L. Matthews, David Nielsen, Nikunj C. Oza

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Reducing Antagonism between Behavioral Diversity and Fitness in Semantic Genetic Programming.

Marcin Szubert, Anuradha Kodali, Sangram Ganguly, Kamalika Das, Josh C. Bongard

Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

Distributed Support Vector Machines: An Overview.

Marco Stolpe, Kanishka Bhaduri, Kamalika Das

Proceedings of the Solving Large Scale Learning Tasks. Challenges and Algorithms, 2016

2015

PerCCS: person-count from carbon dioxide using sparse non-negative matrix factorization.

Chandrayee Basu, Christian Koehler, Kamalika Das, Anind K. Dey

Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2015

Large scale support vector regression for aviation safety.

Kamalika Das, Kanishka Bhaduri, Bryan L. Matthews, Nikunj C. Oza

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014

Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms.

Bryan L. Matthews, Santanu Das, Kanishka Bhaduri, Kamalika Das, Rodney Martin, Nikunj C. Oza

J. Aerosp. Inf. Syst., 2014

Localizing anomalous changes in time-evolving graphs.

Kumar Sricharan, Kamalika Das

Proceedings of the International Conference on Management of Data, 2014

2013

Sparse inverse kernel Gaussian Process regression.

Kamalika Das, Ashok N. Srivastava

Stat. Anal. Data Min., 2013

Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines.

Marco Stolpe, Kanishka Bhaduri, Kamalika Das, Katharina Morik

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

2011

Distributed anomaly detection using 1-class SVM for vertically partitioned data.

Kamalika Das, Kanishka Bhaduri, Petr Votava

Stat. Anal. Data Min., 2011

Scalable, asynchronous, distributed eigen monitoring of astronomy data streams.

Kanishka Bhaduri, Kamalika Das, Kirk D. Borne, Chris Giannella, Tushar Mahule, Hillol Kargupta

Stat. Anal. Data Min., 2011

Multi-objective optimization based privacy preserving distributed data mining in Peer-to-Peer networks.

Kamalika Das, Kanishka Bhaduri, Hillol Kargupta

Peer-to-Peer Netw. Appl., 2011

Distributed Monitoring of the R2 Statistic for Linear Regression.

Kanishka Bhaduri, Kamalika Das, Chris Giannella

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Detecting Abnormal Machine Characteristics in Cloud Infrastructures.

Kanishka Bhaduri, Kamalika Das, Bryan L. Matthews

Proceedings of the Data Mining Workshops (ICDMW), 2011

Sparse Inverse Gaussian Process Regression with Application to Climate Network Discovery.

Kamalika Das, Ashok N. Srivastava

Proceedings of the 2011 Conference on Intelligent Data Understanding, 2011

2010

A local asynchronous distributed privacy preserving feature selection algorithm for large peer-to-peer networks.

Kamalika Das, Kanishka Bhaduri, Hillol Kargupta

Knowl. Inf. Syst., 2010

Block-GP: Scalable Gaussian Process Regression for Multimodal Data.

Kamalika Das, Ashok N. Srivastava

Proceedings of the ICDM 2010, 2010

Distributed Anomaly Detection using Satellite Data From Multiple Modalitie.

Kanishka Bhaduri, Kamalika Das, Petr Votava

Proceedings of the 2010 Conference on Intelligent Data Understanding, 2010

2009

Scalable Distributed Change Detection from Astronomy Data Streams Using Local, Asynchronous Eigen Monitoring Algorithms.

Kamalika Das, Kanishka Bhaduri, Sugandha Arora, Wesley Griffin, Kirk D. Borne, Chris Giannella, Hillol Kargupta

Proceedings of the SIAM International Conference on Data Mining, 2009

A Local Distributed Peer-to-Peer Algorithm Using Multi-Party Optimization Based Privacy Preservation for Data Mining Primitive Computation.

Kamalika Das, Kanishka Bhaduri, Hillol Kargupta

Proceedings of the Proceedings P2P 2009, 2009

2008

Distributed Identification of Top-l Inner Product Elements and its Application in a Peer-to-Peer Network.

Kamalika Das, Kanishka Bhaduri, Kun Liu, Hillol Kargupta

IEEE Trans. Knowl. Data Eng., 2008

Privacy-Preserving Data Analysis on Graphs and Social Networks.

Kun Liu, Kamalika Das, Tyrone Grandison, Hillol Kargupta

Proceedings of the Next Generation of Data Mining., 2008

2007

Algorithms for Distributed Data Stream Mining.

Kanishka Bhaduri, Kamalika Das, Krishnamoorthy Sivakumar, Hillol Kargupta, Ran Wolff, Rong Chen

Proceedings of the Data Streams - Models and Algorithms, 2007

Multi-party, Privacy-Preserving Distributed Data Mining Using a Game Theoretic Framework.

Hillol Kargupta, Kamalika Das, Kun Liu

Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Peer-to-Peer Data Mining, Privacy Issues, and Games.

Kanishka Bhaduri, Kamalika Das, Hillol Kargupta

Proceedings of the Autonomous Intelligent Systems: Multi-Agents and Data Mining, 2007

2006

Client-side web mining for community formation in peer-to-peer environments.

Kun Liu, Kanishka Bhaduri, Kamalika Das, Phuong Nguyen, Hillol Kargupta

SIGKDD Explor., 2006