Parikshit Ram - RankMe

102 papers A* 27A 5B 3Misc 1Journal 53Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep Clustering with Associative Memories. CoRR Bishwajit Saha, Dmitry Krotov, Mohammed J. Zaki, Parikshit Ram
2026	A*	`conf`	Language Model Representations for Efficient Few-Shot Tabular Classification. WWW Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne
2026	J	`jnl`	Language Model Representations for Efficient Few-Shot Tabular Classification. CoRR Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne
2025	J	`jnl`	Dense Associative Memory with Epanechnikov Energy. CoRR Benjamin Hoover, Zhaoyang Shi, Krishnakumar Balasubramanian, Dmitry Krotov, Parikshit Ram
2025	J	`jnl`	Finding Clustering Algorithms in the Transformer Architecture. CoRR Kenneth L. Clarkson, Lior Horesh, Takuya Ito, Charlotte Park, Parikshit Ram
2025	A*	`conf`	Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning. ICML Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning. CoRR Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Mitigating Modality Imbalance in Multi-modal Learning via Multi-objective Optimization. CoRR Heshan Devaka Fernando, Parikshit Ram, Yi Zhou, Soham Dan, Horst Samulowitz, Nathalie Baracaldo, Tianyi Chen
2025	J	`jnl`	Modern Methods in Associative Memory. CoRR Dmitry Krotov, Benjamin Hoover, Parikshit Ram, Bao Pham
2025	A*	`conf`	Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations. AAAI Stephen Carrow, Kyle Erwin, Olga Vilenskaia, Parikshit Ram, Tim Klinger, Naweed Khan, Ndivhuwo Makondo, Alexander G. Gray
2025	J	`jnl`	On Learning Representations for Tabular Data Distillation. CoRR Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne
2025	J	`jnl`	On Learning Representations for Tabular Data Distillation. Trans. Mach. Learn. Res. Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne
2025	J	`jnl`	On the Utility of Existing Fine-Tuned Models on Data-Scarce Domains. Trans. Mach. Learn. Res. Md. Ibrahim Ibne Alam, Parikshit Ram, Soham Dan, Horst Samulowitz, Koushik Kar
2025	A*	`conf`	Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. EMNLP Changsheng Wang, Chongyu Fan, Yihua Zhang, Jinghan Jia, Dennis Wei, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. CoRR Changsheng Wang, Chongyu Fan, Yihua Zhang, Jinghan Jia, Dennis Wei, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Transformers Learn Faster with Semantic Focus. CoRR Parikshit Ram, Kenneth L. Clarkson, Tim Klinger, Shashanka Ubaru, Alexander G. Gray
2024	—	`conf`	Byzantine-Resilient Bilevel Federated Learning. SAM Momin Abbas, Yi Zhou, Nathalie Baracaldo, Horst Samulowitz, Parikshit Ram, Theodoros Salonidis
2024	A*	`conf`	Dense Associative Memory Through the Lens of Random Features. NeurIPS Benjamin Hoover, Duen Horng Chau, Hendrik Strobelt, Parikshit Ram, Dmitry Krotov
2024	J	`jnl`	Dense Associative Memory Through the Lens of Random Features. CoRR Benjamin Hoover, Duen Horng Chau, Hendrik Strobelt, Parikshit Ram, Dmitry Krotov
2024	A*	`conf`	Effective Data Distillation for Tabular Datasets (Student Abstract). AAAI Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne
2024	A	`conf`	Enhancing In-context Learning via Linear Probe Calibration. AISTATS Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen
2024	J	`jnl`	Enhancing In-context Learning via Linear Probe Calibration. CoRR Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen
2024	J	`jnl`	Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning. CoRR Heshan Devaka Fernando, Han Shen, Parikshit Ram, Yi Zhou, Horst Samulowitz, Nathalie Baracaldo, Tianyi Chen
2024	J	`jnl`	Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual Explanations. CoRR Stephen Carrow, Kyle Harper Erwin, Olga Vilenskaia, Parikshit Ram, Tim Klinger, Naweed Aghmad Khan, Ndivhuwo Makondo, Alexander Gray
2024	J	`jnl`	On the Utility of Domain-Adjacent Fine-Tuned Model Ensembles for Few-shot Problems. CoRR Md. Ibrahim Ibne Alam, Parikshit Ram, Soham Dan, Horst Samulowitz, Koushik Kar
2024	J	`jnl`	Quantifying artificial intelligence through algebraic generalization. CoRR Takuya Ito, Murray Campbell, Lior Horesh, Tim Klinger, Parikshit Ram
2024	J	`jnl`	The Importance of Positional Encoding Initialization in Transformers for Relational Reasoning. CoRR Takuya Ito, Luca Cocchi, Tim Klinger, Parikshit Ram, Murray Campbell, Luke J. Hearne
2024	A*	`conf`	WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. NeurIPS Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2024	J	`jnl`	WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. CoRR Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2024	A*	`conf`	What Makes Models Compositional? A Theoretical View. IJCAI Parikshit Ram, Tim Klinger, Alexander G. Gray
2024	—	`conf`	What makes Models Compositional? A Neuro-Symbolic Theoretical View (Extended Abstract). LNSAI@IJCAI Parikshit Ram, Tim Klinger, Alexander G. Gray
2024	J	`jnl`	What makes Models Compositional? A Theoretical View: With Supplement. CoRR Parikshit Ram, Tim Klinger, Alexander G. Gray
2023	J	`jnl`	Compositional Program Generation for Systematic Generalization. CoRR Tim Klinger, Luke Liu, Soham Dan, Maxwell Crouse, Parikshit Ram, Alexander Gray
2023	A*	`conf`	End-to-end Differentiable Clustering with Associative Memories. ICML Bishwajit Saha, Dmitry Krotov, Mohammed J. Zaki, Parikshit Ram
2023	J	`jnl`	End-to-end Differentiable Clustering with Associative Memories. CoRR Bishwajit Saha, Dmitry Krotov, Mohammed J. Zaki, Parikshit Ram
2023	A*	`conf`	Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning. ICLR Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng
2023	J	`jnl`	Model Sparsification Can Simplify Machine Unlearning. CoRR Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
2023	A*	`conf`	Model Sparsity Can Simplify Machine Unlearning. NeurIPS Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
2023	Misc	`conf`	Runtime Prediction of Machine Learning Algorithms in Automl Systems. ICASSP Parijat Dube, Theodoros Salonidis, Parikshit Ram, Ashish Verma
2023	—	`conf`	Searching for Fairer Machine Learning Ensembles. AutoML Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar
2023	A*	`conf`	Single-shot General Hyper-parameter Optimization for Federated Learning. ICLR Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig
2023	A	`conf`	Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. SDM Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble
2023	J	`jnl`	Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. CoRR Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble
2023	A*	`conf`	What Is Missing in IRM Training and Evaluation? Challenges and Solutions. ICLR Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu
2023	J	`jnl`	What Is Missing in IRM Training and Evaluation? Challenges and Solutions. CoRR Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu
2023	B	`conf`	xCloudServing: Automated ML Serving Across Clouds. CLOUD Malgorzata Lazuka, Andreea Anghel, Parikshit Ram, Haralampos Pozidis, Thomas P. Parnell
2022	A*	`conf`	Advancing Model Pruning via Bi-level Optimization. NeurIPS Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
2022	J	`jnl`	Advancing Model Pruning via Bi-level Optimization. CoRR Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
2022	J	`jnl`	An Empirical Study of Modular Bias Mitigators and Ensembles. CoRR Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar
2022	A*	`conf`	Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization. AAAI Akihiro Kishimoto, Djallel Bouneffouf, Radu Marinescu, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Paulito P. Palmes, Adi Botea
2022	A*	`conf`	Federated Nearest Neighbor Classification with a Colony of Fruit-Flies. AAAI Parikshit Ram, Kaushik Sinha
2022	A*	`conf`	Gradual AutoML using Lale. KDD Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar, Jason Tsay
2022	A*	`conf`	Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations. IJCAI Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu
2022	J	`jnl`	Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning. CoRR Alex Gu, Songtao Lu, Parikshit Ram, Lily Weng
2022	J	`jnl`	Navigating Ensemble Configurations for Algorithmic Fairness. CoRR Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar
2022	—	`conf`	On the Optimality Gap of Warm-Started Hyperparameter Optimization. AutoML Parikshit Ram
2022	—	`conf`	Overcoming Catastrophic Forgetting via Direction-Constrained Optimization. ECML/PKDD (1) Yunfei Teng, Anna Choromanska, Murray Campbell, Songtao Lu, Parikshit Ram, Lior Horesh
2022	J	`jnl`	Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis. CoRR Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig
2021	J	`jnl`	Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization. CoRR Paulito P. Palmes, Akihiro Kishimoto, Radu Marinescu, Parikshit Ram, Elizabeth Daly
2021	J	`jnl`	FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning. CoRR Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig
2021	J	`jnl`	Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With Supplement. CoRR Parikshit Ram, Kaushik Sinha
2021	A*	`conf`	Fruit-fly Inspired Neighborhood Encoding for Classification. KDD Kaushik Sinha, Parikshit Ram
2021	—	`conf`	HyperASPO: Fusion of Model and Hyper Parameter Optimization for Multi-objective Machine Learning. IEEE BigData Aswin Kannan, Anamitra Roy Choudhury, Vaibhav Saxena, Saurabh Raje, Parikshit Ram, Ashish Verma, Yogish Sabharwal
2021	A*	`conf`	Pipeline Combinators for Gradual AutoML. NeurIPS Guillaume Baudart, Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar, Jason Tsay
2021	A*	`conf`	Searching for Machine Learning Pipelines Using a Context-Free Grammar. AAAI Radu Marinescu, Akihiro Kishimoto, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Paulito P. Palmes, Adi Botea
2021	J	`jnl`	Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGD. CoRR Chen Fan, Parikshit Ram, Sijia Liu
2020	A*	`conf`	An ADMM Based Framework for AutoML Pipeline Configuration. AAAI Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Dakuo Wang, Andrew Conn, Alexander G. Gray
2020	—	`conf`	AutoAI: Automating the End-to-End AI Lifecycle with Humans-in-the-Loop. IUI Companion 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
2020	A*	`conf`	Exploring Context-Free Languages via Planning: The Case for Automating Machine Learning. ICAPS Michael Katz, Parikshit Ram, Shirin Sohrabi, Octavian Udrea
2020	J	`jnl`	Lale: Consistent Automated Machine Learning. CoRR Guillaume Baudart, Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar
2020	J	`jnl`	Learned Fine-Tuner for Incongruous Few-Shot Learning. CoRR Pu Zhao, Sijia Liu, Parikshit Ram, Songtao Lu, Djallel Bouneffouf, Xue Lin
2020	J	`jnl`	Neural Neighborhood Encoding for Classification. CoRR Kaushik Sinha, Parikshit Ram
2020	J	`jnl`	Solving Constrained CASH Problems with ADMM. CoRR Parikshit Ram, Sijia Liu, Deepak Vijaykeerthy, Dakuo Wang, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Alexander G. Gray
2020	B	`conf`	Survey on Automated End-to-End Data Science? IJCNN 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
2019	J	`jnl`	Automated Machine Learning via ADMM. CoRR Sijia Liu, Parikshit Ram, Djallel Bouneffouf, Gregory Bramble, Andrew R. Conn, Horst Samulowitz, Alexander G. Gray
2019	J	`jnl`	How can AI Automate End-to-End Data Science? CoRR 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
2019	J	`jnl`	Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI. CoRR Dakuo Wang, Justin D. Weisz, Michael J. Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla R. Tausczik, Horst Samulowitz, Alexander G. Gray
2019	J	`jnl`	Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI. Proc. ACM Hum. Comput. Interact. Dakuo Wang, Justin D. Weisz, Michael J. Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla R. Tausczik, Horst Samulowitz, Alexander G. Gray
2019	A*	`conf`	Revisiting kd-tree for Nearest Neighbor Search. KDD Parikshit Ram, Kaushik Sinha
2019	J	`jnl`	Type-Driven Automated Learning with Lale. CoRR Martin Hirzel, Kiran Kate, Avraham Shinnar, Subhrajit Roy, Parikshit Ram
2018	J	`jnl`	Improved maximum inner product search with better theoretical guarantee using randomized partition trees. Mach. Learn. Omid Keivani, Kaushik Sinha, Parikshit Ram
2017	—	`conf`	Fraud Detection with Density Estimation Trees. ADF@KDD Parikshit Ram, Alexander G. Gray
2017	B	`conf`	Improved maximum inner product search with better theoretical guarantees. IJCNN Omid Keivani, Kaushik Sinha, Parikshit Ram
2015	J	`jnl`	Plug-and-play dual-tree algorithm runtime analysis. CoRR Ryan R. Curtin, Dongryeol Lee, William B. March, Parikshit Ram
2015	J	`jnl`	Plug-and-play dual-tree algorithm runtime analysis. J. Mach. Learn. Res. Ryan R. Curtin, Dongryeol Lee, William B. March, Parikshit Ram
2014	J	`jnl`	Dual-tree fast exact max-kernel search. Stat. Anal. Data Min. Ryan R. Curtin, Parikshit Ram
2013	A	`conf`	Fast Exact Max-Kernel Search. SDM Ryan R. Curtin, Alexander G. Gray, Parikshit Ram
2013	J	`jnl`	MLPACK: a scalable C++ machine learning library. J. Mach. Learn. Res. Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray
2013	—	`—`	New paradigms for approximate nearest-neighbor search. Parikshit Ram
2013	J	`jnl`	Tree-Independent Dual-Tree Algorithms CoRR Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles Lee Isbell Jr.
2013	—	`conf`	Tree-Independent Dual-Tree Algorithms. ICML (3) Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles L. Isbell Jr.
2013	—	`conf`	Which Space Partitioning Tree to Use for Search? NIPS Parikshit Ram, Alexander G. Gray
2012	A	`conf`	Efficient retrieval of recommendations in a matrix factorization framework. CIKM Noam Koenigstein, Parikshit Ram, Yuval Shavitt
2012	J	`jnl`	Fast Exact Max-Kernel Search CoRR Ryan R. Curtin, Parikshit Ram, Alexander G. Gray
2012	J	`jnl`	MLPACK: A Scalable C++ Machine Learning Library CoRR Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray
2012	J	`jnl`	Maximum Inner-Product Search using Tree Data-structures CoRR Parikshit Ram, Alexander G. Gray
2012	A*	`conf`	Maximum inner-product search using cone trees. KDD Parikshit Ram, Alexander G. Gray
2012	A	`conf`	Nearest-Neighbor Search on a Time Budget via Max-Margin Trees. SDM Parikshit Ram, Dongryeol Lee, Alexander G. Gray
2011	A*	`conf`	Density estimation trees. KDD Parikshit Ram, Alexander G. Gray
2010	A*	`conf`	Fast euclidean minimum spanning tree: algorithm, analysis, and applications. KDD William B. March, Parikshit Ram, Alexander G. Gray
2009	—	`conf`	Linear-time Algorithms for Pairwise Statistical Problems. NIPS Parikshit Ram, Dongryeol Lee, William B. March, Alexander G. Gray
2009	—	`conf`	Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions. NIPS Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray