Shima Imani

According to our database, Shima Imani authored at least 16 papers between 2018 and 2024.

Collaborative distances:

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

2024

Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models.

Maurice Diesendruck, Jianzhe Lin, Shima Imani, Gayathri Mahalingam, Mingyang Xu, Jie Zhao

CoRR, 2024

Exploring Group and Symmetry Principles in Large Language Models.

Shima Imani, Hamid Palangi

CoRR, 2024

2023

DiversiGATE: A Comprehensive Framework for Reliable Large Language Models.

Shima Imani, Ali Beyram, Harsh Shrivastava

CoRR, 2023

Are uGLAD? Time will tell!

Shima Imani, Harsh Shrivastava

CoRR, 2023

MathPrompter: Mathematical Reasoning using Large Language Models.

Shima Imani, Liang Du, Harsh Shrivastava

Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023

tGLAD: A Sparse Graph Recovery Based Approach for Multivariate Time Series Segmentation.

Shima Imani, Harsh Shrivastava

Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023

2020

Novel Primitive for Analyzing Massive Time Series Data Set.

Shima Imani

PhD thesis, 2020

Introducing time series snippets: a new primitive for summarizing long time series.

Shima Imani, Frank Madrid, Wei Ding, Scott E. Crouter, Eamonn J. Keogh

Data Min. Knowl. Discov., 2020

An ultra-fast time series distance measure to allow data mining in more complex real-world deployments.

Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh

Data Min. Knowl. Discov., 2020

Natura: Towards Conversational Analytics for Comparing and Contrasting Time Series.

Shima Imani, Eamonn J. Keogh

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Fitbit for Chickens?: Time Series Data Mining Can Increase the Productivity of Poultry Farms.

Alireza Abdoli, Sara Alaee, Shima Imani, Amy C. Murillo, Alec C. Gerry, Leslie Hickle, Eamonn J. Keogh

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

2019

Putting the Human in the Time Series Analytics Loop.

Shima Imani, Sara Alaee, Eamonn J. Keogh

Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

Matrix Profile XIX: Time Series Semantic Motifs: A New Primitive for Finding Higher-Level Structure in Time Series.

Shima Imani, Eamonn J. Keogh

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Matrix Profile XX: Finding and Visualizing Time Series Motifs of All Lengths using the Matrix Profile.

Frank Madrid, Shima Imani, Ryan Mercer, Zachary Zimmerman, Nader Shakibay Senobari, Eamonn J. Keogh

Proceedings of the 2019 IEEE International Conference on Big Knowledge, 2019

2018

Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios.

Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh

Proceedings of the IEEE International Conference on Data Mining, 2018

Matrix Profile XIII: Time Series Snippets: A New Primitive for Time Series Data Mining.

Shima Imani, Frank Madrid, Wei Ding, Scott E. Crouter, Eamonn J. Keogh

Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018