Ram, Parikshit

40 publications

ICLRW 2025 Deep Clustering with Associative Memories Bishwajit Saha, Dmitry Krotov, Mohammed J Zaki, Parikshit Ram

NeurIPS 2025 Dense Associative Memory with Epanechnikov Energy Benjamin Hoover, Zhaoyang Shi, Krishna Balasubramanian, Dmitry Krotov, Parikshit Ram

ICLRW 2025 Dense Associative Memory with Epanechnikov Energy Benjamin Hoover, Krishna Balasubramanian, Dmitry Krotov, Parikshit Ram

ICML 2025 Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu

AAAI 2025 Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations Stephen Carrow, Kyle Erwin, Olga Vilenskaia, Parikshit Ram, Tim Klinger, Naweed Khan, Ndivhuwo Makondo, Alexander G. Gray

TMLR 2025 On Learning Representations for Tabular Data Distillation Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne

TMLR 2025 On the Utility of Existing Fine-Tuned Models on Data-Scarce Domains Md Ibrahim Ibne Alam, Parikshit Ram, Soham Dan, Horst Samulowitz, Koushik Kar

NeurIPS 2025 Transformers Learn Faster with Semantic Focus Parikshit Ram, Kenneth L. Clarkson, Tim Klinger, Shashanka Ubaru, Alexander G. Gray

NeurIPSW 2024 Deep Clustering with Associative Memories Bishwajit Saha, Dmitry Krotov, Mohammed J Zaki, Parikshit Ram

NeurIPS 2024 Dense Associative Memory Through the Lens of Random Features Benjamin Hoover, Duen Horng Chau, Hendrik Strobelt, Parikshit Ram, Dmitry Krotov

AAAI 2024 Effective Data Distillation for Tabular Datasets (Student Abstract) Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne

AISTATS 2024 Enhancing In-Context Learning via Linear Probe Calibration Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen

NeurIPS 2024 WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu

IJCAI 2024 What Makes Models Compositional? a Theoretical View Parikshit Ram, Tim Klinger, Alexander G. Gray

ICML 2023 End-to-End Differentiable Clustering with Associative Memories Bishwajit Saha, Dmitry Krotov, Mohammed J Zaki, Parikshit Ram

ICMLW 2023 End-to-End Differentiable Clustering with Associative Memories Bishwajit Saha, Dmitry Krotov, Mohammed J Zaki, Parikshit Ram

ICLR 2023 Min-Max Multi-Objective Bilevel Optimization with Applications in Robust Machine Learning Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng

NeurIPS 2023 Model Sparsity Can Simplify Machine Unlearning Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

AutoML 2023 Searching for Fairer Machine Learning Ensembles Michael Feffer, Martin Hirzel, Samuel C Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

ICLR 2023 Single-Shot General Hyper-Parameter Optimization for Federated Learning Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

ICLR 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

NeurIPS 2022 Advancing Model Pruning via Bi-Level Optimization Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu

AAAI 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

AAAI 2022 Federated Nearest Neighbor Classification with a Colony of Fruit-Flies Parikshit Ram, Kaushik Sinha

IJCAI 2022 Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu

AutoML 2022 On the Optimality Gap of Warm-Started Hyperparameter Optimization Parikshit Ram

ECML-PKDD 2022 Overcoming Catastrophic Forgetting via Direction-Constrained Optimization Yunfei Teng, Anna Choromanska, Murray Campbell, Songtao Lu, Parikshit Ram, Lior Horesh

ICMLW 2021 Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization Akihiro Kishimoto, Djallel Bouneffouf, Radu Marinescu, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Paulito Pedregosa Palmes, Adi Botea

ICMLW 2021 Leveraging Theoretical Tradeoffs in Hyperparameter Selection for Improved Empirical Performance Parikshit Ram, Alexander G. Gray, Horst Samulowitz

NeurIPS 2021 Pipeline Combinators for Gradual AutoML Guillaume Baudart, Martin Hirzel, Kiran Kate, Parikshit Ram, Avi Shinnar, Jason Tsay

AAAI 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

NeurIPSW 2021 Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGD Chen Fan, Parikshit Ram, Sijia Liu

AAAI 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

MLJ 2018 Improved Maximum Inner Product Search with Better Theoretical Guarantee Using Randomized Partition Trees Omid Keivani, Kaushik Sinha, Parikshit Ram

JMLR 2015 Plug-and-Play Dual-Tree Algorithm Runtime Analysis Ryan R. Curtin, Dongryeol Lee, William B. March, Parikshit Ram

MLOSS 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

ICML 2013 Tree-Independent Dual-Tree Algorithms Ryan Curtin, William March, Parikshit Ram, David Anderson, Alexander Gray, Charles Isbell

NeurIPS 2013 Which Space Partitioning Tree to Use for Search? Parikshit Ram, Alexander Gray

NeurIPS 2009 Linear-Time Algorithms for Pairwise Statistical Problems Parikshit Ram, Dongryeol Lee, William March, Alexander G. Gray

NeurIPS 2009 Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray