Parikshit Ram
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
32
Venues
13
Active years
2010–2026
Best venue rank
A*
Where they publish
Papers
32 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | WWW | Language Model Representations for Efficient Few-Shot Tabular Classification. | Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne |
| 2025 | AAAI | 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 |
| 2025 | EMNLP | Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. | Changsheng Wang, Chongyu Fan, Yihua Zhang, Jinghan Jia, Dennis Wei, Parikshit Ram, Nathalie Baracaldo, Sijia Liu |
| 2025 | ICML | 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 |
| 2024 | AAAI | Effective Data Distillation for Tabular Datasets (Student Abstract). | Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne |
| 2024 | AISTATS | Enhancing In-context Learning via Linear Probe Calibration. | Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen |
| 2024 | IJCAI | What Makes Models Compositional? A Theoretical View. | Parikshit Ram, Tim Klinger, Alexander G. Gray |
| 2023 | ICASSP | Runtime Prediction of Machine Learning Algorithms in Automl Systems. | Parijat Dube, Theodoros Salonidis, Parikshit Ram, Ashish Verma |
| 2023 | ICLR | Single-shot General Hyper-parameter Optimization for Federated Learning. | Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig |
| 2023 | ICLR | Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning. | Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng |
| 2023 | ICLR | What Is Missing in IRM Training and Evaluation? Challenges and Solutions. | Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu |
| 2023 | ICML | End-to-end Differentiable Clustering with Associative Memories. | Bishwajit Saha, Dmitry Krotov, Mohammed J. Zaki, Parikshit Ram |
| 2023 | SDM | Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. | Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble |
| 2022 | AAAI | 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 |
| 2022 | AAAI | Federated Nearest Neighbor Classification with a Colony of Fruit-Flies. | Parikshit Ram, Kaushik Sinha |
| 2022 | IJCAI | Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations. | Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu |
| 2022 | KDD | Gradual AutoML using Lale. | Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar, Jason Tsay |
| 2021 | AAAI | 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 |
| 2021 | KDD | Fruit-fly Inspired Neighborhood Encoding for Classification. | Kaushik Sinha, Parikshit Ram |
| 2020 | AAAI | 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 |
| 2020 | IJCNN | 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 |
| 2020 | IUI | 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 |
| 2019 | KDD | Revisiting kd-tree for Nearest Neighbor Search. | Parikshit Ram, Kaushik Sinha |
| 2017 | IJCNN | Improved maximum inner product search with better theoretical guarantees. | Omid Keivani, Kaushik Sinha, Parikshit Ram |
| 2017 | KDD | Fraud Detection with Density Estimation Trees. | Parikshit Ram, Alexander G. Gray |
| 2013 | ICML | Tree-Independent Dual-Tree Algorithms. | Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles L. Isbell Jr. |
| 2013 | SDM | Fast Exact Max-Kernel Search. | Ryan R. Curtin, Alexander G. Gray, Parikshit Ram |
| 2012 | CIKM | Efficient retrieval of recommendations in a matrix factorization framework. | Noam Koenigstein, Parikshit Ram, Yuval Shavitt |
| 2012 | KDD | Maximum inner-product search using cone trees. | Parikshit Ram, Alexander G. Gray |
| 2012 | SDM | Nearest-Neighbor Search on a Time Budget via Max-Margin Trees. | Parikshit Ram, Dongryeol Lee, Alexander G. Gray |
| 2011 | KDD | Density estimation trees. | Parikshit Ram, Alexander G. Gray |
| 2010 | KDD | Fast euclidean minimum spanning tree: algorithm, analysis, and applications. | William B. March, Parikshit Ram, Alexander G. Gray |