Kamalika Das

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 24

Top Topics

Aviation Safety

Diffusion Model

Top Venues

Publications

Jiaxin Zhang, Kamalika Das, Kumar Sricharan
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. AISTATS (2024)
Xiang Gao, Kamalika Das
Customizing Language Model Responses with Contrastive In-Context Learning. AAAI (2024)
Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das
SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. CoRR (2024)
Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das
SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. EACL (1) (2024)
Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models. CoRR (2024)
Wendi Cui, Jiaxin Zhang, Zhuohang Li, Lopez Damien, Kamalika Das, Bradley A. Malin, Kumar Sricharan
DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models. CoRR (2024)
Xiang Gao, Kamalika Das
Customizing Language Model Responses with Contrastive In-Context Learning. CoRR (2024)
Magesh Rajasekaran, Md Saiful Islam Sajol, Frej Berglind, Supratik Mukhopadhyay, Kamalika Das
COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification. SDM (2024)
Jiaxin Zhang, Kamalika Das, Kumar Sricharan
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. CoRR (2024)
Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan
DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. WACV (2024)
Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan
Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. NeurIPS (2023)
Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan
DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. CoRR (2023)
Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan
SAC³: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency. EMNLP (Findings) (2023)
Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan
Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. CoRR (2023)
Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan
: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency. CoRR (2023)
Frej Berglind, Haron Temam, Supratik Mukhopadhyay, Kamalika Das, Md Saiful Islam Sajol, Kumar Sricharan, Kumar Kallurupalli
XOOD: Extreme Value Based Out-Of-Distribution Detection For Image Classification. CoRR (2022)
Ata Akbari Asanjan, Kamalika Das, Alan S. Li, Ved Chirayath, Juan Torres-Perez, Soroosh Sorooshian
Learning Instrument Invariant Characteristics for Generating High-resolution Global Coral Reef Maps. KDD (2020)
Aniruddha Basak, Kamalika Das, Ole J. Mengshoel
CADDeLaG: Framework for distributed anomaly detection in large dense graph sequences. CoRR (2018)
Anuradha Kodali, Marcin Szubert, Kamalika Das, Sangram Ganguly, Joshua Clifford Bongard
Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis. PPSN (1) (2018)
Kamalika Das, Ilya Avrekh, Bryan L. Matthews, Manali Sharma, Nikunj C. Oza
ASK-the-Expert: Active Learning Based Knowledge Discovery Using the Expert. ECML/PKDD (3) (2017)
Marco Stolpe, Kanishka Bhaduri, Kamalika Das
Distributed Support Vector Machines: An Overview. Solving Large Scale Learning Tasks (2016)
Marcin Szubert, Anuradha Kodali, Sangram Ganguly, Kamalika Das, Josh C. Bongard
Semantic Forward Propagation for Symbolic Regression. PPSN (2016)
Manali Sharma, Kamalika Das, Mustafa Bilgic, Bryan L. Matthews, David Nielsen, Nikunj C. Oza
Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation. ECML/PKDD (3) (2016)
Marcin Szubert, Anuradha Kodali, Sangram Ganguly, Kamalika Das, Josh C. Bongard
Reducing Antagonism between Behavioral Diversity and Fitness in Semantic Genetic Programming. GECCO (2016)
Kamalika Das, Kanishka Bhaduri, Bryan L. Matthews, Nikunj C. Oza
Large scale support vector regression for aviation safety. IEEE BigData (2015)
Chandrayee Basu, Christian Koehler, Kamalika Das, Anind K. Dey
PerCCS: person-count from carbon dioxide using sparse non-negative matrix factorization. UbiComp (2015)
Kumar Sricharan, Kamalika Das
Localizing anomalous changes in time-evolving graphs. SIGMOD Conference (2014)
Bryan L. Matthews, Santanu Das, Kanishka Bhaduri, Kamalika Das, Rodney Martin, Nikunj C. Oza
Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms. J. Aerosp. Inf. Syst. 11 (7) (2014)
Marco Stolpe, Kanishka Bhaduri, Kamalika Das, Katharina Morik
Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines. ECML/PKDD (3) (2013)
Bryan L. Matthews, Santanu Das, Kanishka Bhaduri, Kamalika Das, Rodney Martin, Nikunj C. Oza
Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms. J. Aerosp. Inf. Syst. 10 (10) (2013)
Kamalika Das, Ashok N. Srivastava
Sparse inverse kernel Gaussian Process regression. Stat. Anal. Data Min. 6 (3) (2013)
Kamalika Das, Ashok N. Srivastava
Sparse Inverse Gaussian Process Regression with Application to Climate Network Discovery. CIDU (2011)
Kanishka Bhaduri, Kamalika Das, Kirk D. Borne, Chris Giannella, Tushar Mahule, Hillol Kargupta
Scalable, asynchronous, distributed eigen monitoring of astronomy data streams. Stat. Anal. Data Min. 4 (3) (2011)
Kamalika Das, Kanishka Bhaduri, Petr Votava
Distributed anomaly detection using 1-class SVM for vertically partitioned data. Stat. Anal. Data Min. 4 (4) (2011)
Kamalika Das, Kanishka Bhaduri, Hillol Kargupta
Multi-objective optimization based privacy preserving distributed data mining in Peer-to-Peer networks. Peer-to-Peer Netw. Appl. 4 (2) (2011)
Kanishka Bhaduri, Kamalika Das, Chris Giannella
Distributed Monitoring of the R2 Statistic for Linear Regression. SDM (2011)
Kanishka Bhaduri, Kamalika Das, Bryan L. Matthews
Detecting Abnormal Machine Characteristics in Cloud Infrastructures. ICDM Workshops (2011)
Kanishka Bhaduri, Kamalika Das, Petr Votava
Distributed Anomaly Detection using Satellite Data From Multiple Modalitie. CIDU (2010)
Kamalika Das, Ashok N. Srivastava
Block-GP: Scalable Gaussian Process Regression for Multimodal Data. ICDM (2010)
Kamalika Das, Kanishka Bhaduri, Hillol Kargupta
A local asynchronous distributed privacy preserving feature selection algorithm for large peer-to-peer networks. Knowl. Inf. Syst. 24 (3) (2010)
Kamalika Das, Kanishka Bhaduri, Sugandha Arora, Wesley Griffin, Kirk D. Borne, Chris Giannella, Hillol Kargupta
Scalable Distributed Change Detection from Astronomy Data Streams Using Local, Asynchronous Eigen Monitoring Algorithms. SDM (2009)
Kamalika Das, Kanishka Bhaduri, Hillol Kargupta
A Local Distributed Peer-to-Peer Algorithm Using Multi-Party Optimization Based Privacy Preservation for Data Mining Primitive Computation. Peer-to-Peer Computing (2009)
Kamalika Das, Kanishka Bhaduri, Kun Liu, Hillol Kargupta
Distributed Identification of Top-l Inner Product Elements and its Application in a Peer-to-Peer Network. IEEE Trans. Knowl. Data Eng. 20 (4) (2008)
Hillol Kargupta, Kamalika Das, Kun Liu
Multi-party, Privacy-Preserving Distributed Data Mining Using a Game Theoretic Framework. PKDD (2007)
Kanishka Bhaduri, Kamalika Das, Hillol Kargupta
Peer-to-Peer Data Mining, Privacy Issues, and Games. AIS-ADM (2007)
Kun Liu, Kanishka Bhaduri, Kamalika Das, Phuong Nguyen, Hillol Kargupta
Client-side web mining for community formation in peer-to-peer environments. SIGKDD Explor. 8 (2) (2006)