← Authors

Parikshit Ram

28 papers · 2009–2025 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (17) 🧭 Keyword Pioneer 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (16) 🐝 Cross-Pollinator (9) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ† Keyword Champion (3) ⚑ Prolific Year (5) πŸš€ Conference Pioneer ❓ The Questioner (3) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (124) πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (28)

Conferences

NIPS (8) AAAI (6) ICLR (3) ICML (3) AUTOML (2) IJCAI (2) JMLR (2) AISTATS (1) EMNLP (1)

Top co-authors

Sijia Liu (8) Alexander G. Gray (5) Nathalie Baracaldo (5) Yihua Zhang (5) Yuguang Yao (4) Horst Samulowitz (4) Jinghan Jia (4) Dongryeol Lee (3) Yi Zhou (3) Alexander Gray (3)

Keywords

pipeline optimization (4) hyperparameter optimization (4) machine unlearning (3) automated machine learning (3) nearest neighbor search (3) few-shot learning (2) dual-tree algorithm (2) associative memory (2) cover tree (2) knowledge editing (1) gradient-based optimization (1) lottery ticket hypothesis (1) differential privacy (1) in-context learning (1) similarity search (1) ensemble learning (1) learning theory (1) feature importance (1) model editing (1) black-box optimization (1)

Papers

Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills EMNLP 2025
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning ICML 2025
Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations AAAI 2025
What Makes Models Compositional? A Theoretical View IJCAI 2024
Dense Associative Memory Through the Lens of Random Features NIPS 2024
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models NIPS 2024
Effective Data Distillation for Tabular Datasets (Student Abstract) AAAI 2024
Enhancing In-context Learning via Linear Probe Calibration AISTATS 2024
End-to-end Differentiable Clustering with Associative Memories ICML 2023
Model Sparsity Can Simplify Machine Unlearning NIPS 2023
Searching for Fairer Machine Learning Ensembles AUTOML 2023
Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning ICLR 2023
What Is Missing in IRM Training and Evaluation? Challenges and Solutions ICLR 2023
Single-shot General Hyper-parameter Optimization for Federated Learning ICLR 2023
Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization AAAI 2022
On the Optimality Gap of Warm-Started Hyperparameter Optimization AUTOML 2022
Advancing Model Pruning via Bi-level Optimization NIPS 2022
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations IJCAI 2022
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies AAAI 2022
Searching for Machine Learning Pipelines Using a Context-Free Grammar AAAI 2021
Pipeline Combinators for Gradual AutoML NIPS 2021
An ADMM Based Framework for AutoML Pipeline Configuration AAAI 2020
Plug-and-Play Dual-Tree Algorithm Runtime Analysis JMLR 2015
Tree-Independent Dual-Tree Algorithms ICML 2013
Which Space Partitioning Tree to Use for Search? NIPS 2013
MLPACK: A Scalable C++ Machine Learning Library JMLR 2013
Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions NIPS 2009
Linear-time Algorithms for Pairwise Statistical Problems NIPS 2009