Toward Information Theoretic Human-Robot Dialog. - Stefanie Tellex; Pratiksha Thaker; Robin Deits; Thomas Kollar; Nicholas Roy (Robotics: Science and Systems, 2012)

Clarifying commands with information-theoretic human-robot dialog. - Robin Deits; Stefanie Tellex; Pratiksha Thaker; Dimitar Simeonov; Thomas Kollar; Nicholas Roy (J. Hum. Robot Interact., 2013)

An experimental study of the learnability of congestion control. - Anirudh Sivaraman; Keith Winstein; Pratiksha Thaker; Hari Balakrishnan (SIGCOMM, 2014)

Learning perceptually grounded word meanings from unaligned parallel data. - Stefanie Tellex; Pratiksha Thaker; Joshua Mason Joseph; Nicholas Roy (Mach. Learn., 2014)

Evaluating End-to-End Optimization for Data Analytics Applications in Weld. - Shoumik Palkar; James Thomas 003; Deepak Narayanan; Pratiksha Thaker; Rahul Palamuttam; Parimarjan Negi; Anil Shanbhag; Malte Schwarzkopf; Holger Pirk; Saman P. Amarasinghe; Samuel Madden 001; Matei Zaharia (Proc. VLDB Endow., 2018)

Clamor: Extending Functional Cluster Computing Frameworks with Fine-Grained Remote Memory Access. - Pratiksha Thaker; Hudson Ayers; Deepti Raghavan; Ning Niu; Philip Alexander Levis; Matei Zaharia (SoCC, 2021)

Don't Hate the Player, Hate the Game: Safety and Utility in Multi-Agent Congestion Control. - Pratiksha Thaker; Matei Zaharia; Tatsunori Hashimoto (HotNets, 2021)

Overlook: Differentially Private Exploratory Visualization for Big Data. - Mihai Budiu; Pratiksha Thaker; Parikshit Gopalan; Udi Wieder; Matei Zaharia (J. Priv. Confidentiality, 2022)

Congestion Control Safety via Comparative Statics. - Pratiksha Thaker; Matei Zaharia; Tatsunori Hashimoto (INFOCOM, 2023)

On Noisy Evaluation in Federated Hyperparameter Tuning. - Kevin Kuo; Pratiksha Thaker; Mikhail Khodak; John Nguyen; Daniel Jiang; Ameet Talwalkar; Virginia Smith (MLSys, 2023)

Cornflakes: Zero-Copy Serialization for Microsecond-Scale Networking. - Deepti Raghavan; Shreya Ravi; Gina Yuan; Pratiksha Thaker; Sanjari Srivastava; Micah Murray; Pedro Henrique Penna; Amy Ousterhout; Philip Alexander Levis; Matei Zaharia; Irene Zhang (SOSP, 2023)

Leveraging Public Representations for Private Transfer Learning. - Pratiksha Thaker; Amrith Setlur; Zhiwei Steven Wu; Virginia Smith (CoRR, 2023)

ALTO: An Efficient Network Orchestrator for Compound AI Systems. - Keshav Santhanam; Deepti Raghavan; Muhammad Shahir Rahman; Thejas Venkatesh; Neha Kunjal; Pratiksha Thaker; Philip Alexander Levis; Matei Zaharia (EuroMLSys@EuroSys, 2024)

On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift. - Pratiksha Thaker; Amrith Setlur; Steven Z. Wu; Virginia Smith (NeurIPS, 2024)

Guardrail Baselines for Unlearning in LLMs. - Pratiksha Thaker; Yash Maurya; Virginia Smith (CoRR, 2024)

Position: LLM Unlearning Benchmarks are Weak Measures of Progress. - Pratiksha Thaker; Shengyuan Hu 001; Neil Kale; Yash Maurya; Zhiwei Steven Wu; Virginia Smith (SaTML, 2025)

Generate-then-Verify: Reconstructing Data from Limited Published Statistics. - Terrance Liu; Eileen Xiao; Pratiksha Thaker; Adam Smith 006; Zhiwei Steven Wu (CoRR, 2025)

Membership Inference Attacks for Unseen Classes. - Pratiksha Thaker; Neil Kale; Zhiwei Steven Wu; Virginia Smith (CoRR, 2025)

Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference. - Terrance Liu; Matteo Boglioni; Yiwei Fu; Shengyuan Hu 001; Pratiksha Thaker; Zhiwei Steven Wu (CoRR, 2025)

BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap. - Shengyuan Hu 001; Neil Kale; Pratiksha Thaker; Yiwei Fu; Steven Wu 001; Virginia Smith (CoRR, 2025)

PARALLELPROMPT: Extracting Parallelism from Large Language Model Queries. - Steven Kolawole; Keshav Santhanam; Virginia Smith; Pratiksha Thaker (CoRR, 2025)

Lower Bounds for Public-Private Learning under Distribution Shift. - Amrith Setlur; Pratiksha Thaker; Jonathan Ullman (CoRR, 2025)