Parikshit Ram

According to our database, Parikshit Ram authored at least 63 papers between 2009 and 2024.

Collaborative distances:

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

2024

Enhancing In-context Learning via Linear Probe Calibration.

Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen

CoRR, 2024

Effective Data Distillation for Tabular Datasets (Student Abstract).

Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne

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

2023

Compositional Program Generation for Systematic Generalization.

Tim Klinger, Luke Liu, Soham Dan, Maxwell Crouse, Parikshit Ram, Alexander Gray

CoRR, 2023

Model Sparsification Can Simplify Machine Unlearning.

Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

CoRR, 2023

Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection.

Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Model Sparsity Can Simplify Machine Unlearning.

Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

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

End-to-end Differentiable Clustering with Associative Memories.

Bishwajit Saha, Dmitry Krotov, Mohammed J. Zaki, Parikshit Ram

Proceedings of the International Conference on Machine Learning, 2023

What Is Missing in IRM Training and Evaluation? Challenges and Solutions.

Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning.

Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Single-shot General Hyper-parameter Optimization for Federated Learning.

Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Runtime Prediction of Machine Learning Algorithms in Automl Systems.

Parijat Dube, Theodoros Salonidis, Parikshit Ram, Ashish Verma

Proceedings of the IEEE International Conference on Acoustics, 2023

Searching for Fairer Machine Learning Ensembles.

Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

Proceedings of the International Conference on Automated Machine Learning, 2023

xCloudServing: Automated ML Serving Across Clouds.

Malgorzata Lazuka, Andreea Anghel, Parikshit Ram, Haralampos Pozidis, Thomas P. Parnell

Proceedings of the 16th IEEE International Conference on Cloud Computing, 2023

2022

Navigating Ensemble Configurations for Algorithmic Fairness.

Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

CoRR, 2022

Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning.

Alex Gu, Songtao Lu, Parikshit Ram, Lily Weng

CoRR, 2022

Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis.

Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

CoRR, 2022

An Empirical Study of Modular Bias Mitigators and Ensembles.

Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

CoRR, 2022

Overcoming Catastrophic Forgetting via Direction-Constrained Optimization.

Yunfei Teng, Anna Choromanska, Murray Campbell, Songtao Lu, Parikshit Ram, Lior Horesh

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Advancing Model Pruning via Bi-level Optimization.

Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Gradual AutoML using Lale.

Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar, Jason Tsay

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations.

Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

On the Optimality Gap of Warm-Started Hyperparameter Optimization.

Parikshit Ram

Proceedings of the International Conference on Automated Machine Learning, 2022

Federated Nearest Neighbor Classification with a Colony of Fruit-Flies.

Parikshit Ram, Kaushik Sinha

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization.

Akihiro Kishimoto, Djallel Bouneffouf, Radu Marinescu, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Paulito P. Palmes, Adi Botea

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning.

Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

CoRR, 2021

Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With Supplement.

Parikshit Ram, Kaushik Sinha

CoRR, 2021

Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGD.

Chen Fan, Parikshit Ram, Sijia Liu

CoRR, 2021

Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization.

Paulito P. Palmes, Akihiro Kishimoto, Radu Marinescu, Parikshit Ram, Elizabeth Daly

CoRR, 2021

Pipeline Combinators for Gradual AutoML.

Guillaume Baudart, Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar, Jason Tsay

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fruit-fly Inspired Neighborhood Encoding for Classification.

Kaushik Sinha, Parikshit Ram

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

HyperASPO: Fusion of Model and Hyper Parameter Optimization for Multi-objective Machine Learning.

Aswin Kannan, Anamitra Roy Choudhury, Vaibhav Saxena, Saurabh Raje, Parikshit Ram, Ashish Verma, Yogish Sabharwal

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Searching for Machine Learning Pipelines Using a Context-Free Grammar.

Radu Marinescu, Akihiro Kishimoto, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Paulito P. Palmes, Adi Botea

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Learned Fine-Tuner for Incongruous Few-Shot Learning.

Pu Zhao, Sijia Liu, Parikshit Ram, Songtao Lu, Djallel Bouneffouf, Xue Lin

CoRR, 2020

Neural Neighborhood Encoding for Classification.

Kaushik Sinha, Parikshit Ram

CoRR, 2020

Lale: Consistent Automated Machine Learning.

Guillaume Baudart, Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar

CoRR, 2020

Solving Constrained CASH Problems with ADMM.

Parikshit Ram, Sijia Liu, Deepak Vijaykeerthy, Dakuo Wang, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Alexander G. Gray

CoRR, 2020

AutoAI: Automating the End-to-End AI Lifecycle with Humans-in-the-Loop.

Dakuo Wang, Parikshit Ram, Daniel Karl I. Weidele, Sijia Liu, Michael J. Muller, Justin D. Weisz, Abel N. Valente, Arunima Chaudhary, Dustin Ramsey Torres, Horst Samulowitz, Lisa Amini

Proceedings of the IUI '20: 25th International Conference on Intelligent User Interfaces, 2020

Survey on Automated End-to-End Data Science?

Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Exploring Context-Free Languages via Planning: The Case for Automating Machine Learning.

Michael Katz, Parikshit Ram, Shirin Sohrabi, Octavian Udrea

Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling, 2020

An ADMM Based Framework for AutoML Pipeline Configuration.

Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Dakuo Wang, Andrew Conn, Alexander G. Gray

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI.

Dakuo Wang, Justin D. Weisz, Michael J. Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla R. Tausczik, Horst Samulowitz, Alexander G. Gray

Proc. ACM Hum. Comput. Interact., 2019

How can AI Automate End-to-End Data Science?

Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray

CoRR, 2019

Type-Driven Automated Learning with Lale.

Martin Hirzel, Kiran Kate, Avraham Shinnar, Subhrajit Roy, Parikshit Ram

CoRR, 2019

Automated Machine Learning via ADMM.

Sijia Liu, Parikshit Ram, Djallel Bouneffouf, Gregory Bramble, Andrew R. Conn, Horst Samulowitz, Alexander G. Gray

CoRR, 2019

Revisiting kd-tree for Nearest Neighbor Search.

Parikshit Ram, Kaushik Sinha

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Improved maximum inner product search with better theoretical guarantee using randomized partition trees.

Omid Keivani, Kaushik Sinha, Parikshit Ram

Mach. Learn., 2018

2017

Fraud Detection with Density Estimation Trees.

Parikshit Ram, Alexander G. Gray

Proceedings of the KDD 2017 Workshop on Anomaly Detection in Finance, 2017

Improved maximum inner product search with better theoretical guarantees.

Omid Keivani, Kaushik Sinha, Parikshit Ram

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2015

Plug-and-play dual-tree algorithm runtime analysis.

Ryan R. Curtin, Dongryeol Lee, William B. March, Parikshit Ram

J. Mach. Learn. Res., 2015

2014

Dual-tree fast exact max-kernel search.

Ryan R. Curtin, Parikshit Ram

Stat. Anal. Data Min., 2014

2013

New paradigms for approximate nearest-neighbor search.

Parikshit Ram

PhD thesis, 2013

MLPACK: a scalable C++ machine learning library.

Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray

J. Mach. Learn. Res., 2013

Fast Exact Max-Kernel Search.

Ryan R. Curtin, Alexander G. Gray, Parikshit Ram

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Which Space Partitioning Tree to Use for Search?

Parikshit Ram, Alexander G. Gray

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Tree-Independent Dual-Tree Algorithms.

Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles L. Isbell Jr.

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Maximum Inner-Product Search using Tree Data-structures

Parikshit Ram, Alexander G. Gray

CoRR, 2012

Nearest-Neighbor Search on a Time Budget via Max-Margin Trees.

Parikshit Ram, Dongryeol Lee, Alexander G. Gray

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Maximum inner-product search using cone trees.

Parikshit Ram, Alexander G. Gray

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Efficient retrieval of recommendations in a matrix factorization framework.

Noam Koenigstein, Parikshit Ram, Yuval Shavitt

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011

Density estimation trees.

Parikshit Ram, Alexander G. Gray

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2010

Fast euclidean minimum spanning tree: algorithm, analysis, and applications.

William B. March, Parikshit Ram, Alexander G. Gray

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009

Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions.

Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Linear-time Algorithms for Pairwise Statistical Problems.

Parikshit Ram, Dongryeol Lee, William B. March, Alexander G. Gray

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009