Microwave workshop for windows. - Colin White (Comput. Educ., 1998)

An Update on PENG Light. - Colin White; Rolf Schwitter (ALTA, 2009)

Small Dynamical Heights for Quadratic Polynomials and Rational Functions. - Robert L. Benedetto; Ruqian Chen; Trevor Hyde; Yordanka Kovacheva; Colin White (Exp. Math., 2014)

Lower Bounds in the Preprocessing and Query Phases of Routing Algorithms. - Colin White (ESA, 2015)

Symmetric and Asymmetric $k$-center Clustering under Stability. - Maria-Florina Balcan; Nika Haghtalab; Colin White (CoRR, 2015)

Lower Bounds on the Query Times of Hub Labeling, Contraction Hierarchies, and Transit Node Routing. - Colin White (CoRR, 2015)

Learning Combinatorial Functions from Pairwise Comparisons. - Maria-Florina Balcan; Ellen Vitercik; Colin White (COLT, 2016)

k-Center Clustering Under Perturbation Resilience. - Maria-Florina Balcan; Nika Haghtalab; Colin White (ICALP, 2016)

Learning the best algorithm for max-cut, clustering, and other partitioning problems. - Maria-Florina Balcan; Vaishnavh Nagarajan; Ellen Vitercik; Colin White (CoRR, 2016)

Data Driven Resource Allocation for Distributed Learning. - Travis Dick; Mu Li 003; Venkata Krishna Pillutla; Colin White; Maria-Florina Balcan; Alexander J. Smola (AAAI Workshops, 2017)

Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems. - Maria-Florina Balcan; Vaishnavh Nagarajan; Ellen Vitercik; Colin White (COLT, 2017)

General and Robust Communication-Efficient Algorithms for Distributed Clustering. - Pranjal Awasthi; Maria-Florina Balcan; Colin White (CoRR, 2017)

Clustering under Local Stability: Bridging the Gap between Worst-Case and Beyond Worst-Case Analysis. - Maria-Florina Balcan; Colin White (CoRR, 2017)

Data-Driven Clustering via Parameterized Lloyd's Families. - Maria-Florina Balcan; Travis Dick; Colin White (NeurIPS, 2018)

Robust Communication-Optimal Distributed Clustering Algorithms. - Pranjal Awasthi; Ainesh Bakshi; Maria-Florina Balcan; Colin White; David P. Woodruff (ICALP, 2019)

Intra-Processing Methods for Debiasing Neural Networks. - Yash Savani; Colin White; Naveen Sundar Govindarajulu (NeurIPS, 2020)

A Study on Encodings for Neural Architecture Search. - Colin White; Willie Neiswanger; Sam Nolen; Yash Savani (NeurIPS, 2020)

Local Search is State of the Art for NAS Benchmarks. - Colin White; Sam Nolen; Yash Savani (CoRR, 2020)

Post-Hoc Methods for Debiasing Neural Networks. - Yash Savani; Colin White; Naveen Sundar Govindarajulu (CoRR, 2020)

k-center Clustering under Perturbation Resilience. - Maria-Florina Balcan; Nika Haghtalab; Colin White (ACM Trans. Algorithms, 2020)

BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search. - Colin White; Willie Neiswanger; Yash Savani (AAAI, 2021)

Synthetic Benchmarks for Scientific Research in Explainable Machine Learning. - Yang Liu; Sujay Khandagale; Colin White; Willie Neiswanger (NeurIPS Datasets and Benchmarks, 2021)

How Powerful are Performance Predictors in Neural Architecture Search? - Colin White; Arber Zela; Robin Ru; Yang Liu; Frank Hutter (NeurIPS, 2021)

NAS-Bench-x11 and the Power of Learning Curves. - Shen Yan; Colin White; Yash Savani; Frank Hutter (NeurIPS, 2021)

Exploring the loss landscape in neural architecture search. - Colin White; Sam Nolen; Yash Savani (UAI, 2021)

How Powerful are Performance Predictors in Neural Architecture Search? - Colin White; Arber Zela; Binxin Ru; Yang Liu; Frank Hutter (CoRR, 2021)

New Aspects of Beyond Worst-Case Analysis. - Colin White (2021)

NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy. - Yash Mehta; Colin White; Arber Zela; Arjun Krishnakumar; Guri Zabergja; Shakiba Moradian; Mahmoud Safari; Kaicheng Yu; Frank Hutter (ICLR, 2022)

NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies. - Arjun Krishnakumar; Colin White; Arber Zela; Renbo Tu; Mahmoud Safari; Frank Hutter (NeurIPS, 2022)

On the Generalizability and Predictability of Recommender Systems. - Duncan C. McElfresh; Sujay Khandagale; Jonathan Valverde; John Dickerson 001; Colin White (NeurIPS, 2022)

AutoML for Climate Change: A Call to Action. - Renbo Tu; Nicholas Roberts; Vishak Prasad; Sibasis Nayak; Paarth Jain; Frederic Sala; Ganesh Ramakrishnan; Ameet Talwalkar; Willie Neiswanger; Colin White (CoRR, 2022)

On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition. - Rhea Sukthanker; Samuel Dooley; John P. Dickerson; Colin White; Frank Hutter; Micah Goldblum (CoRR, 2022)

Speeding up NAS with Adaptive Subset Selection. - Vishak Prasad C.; Colin White; Paarth Jain; Sibasis Nayak; Ganesh Ramakrishnan (CoRR, 2022)

ForecastPFN: Synthetically-Trained Zero-Shot Forecasting. - Samuel Dooley; Gurnoor Singh Khurana; Chirag Mohapatra; Siddartha V. Naidu; Colin White (NeurIPS, 2023)

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition. - Samuel Dooley; Rhea Sukthanker; John P. Dickerson; Colin White; Frank Hutter; Micah Goldblum (NeurIPS, 2023)

When Do Neural Nets Outperform Boosted Trees on Tabular Data? - Duncan C. McElfresh; Sujay Khandagale; Jonathan Valverde; Vishak Prasad C.; Ganesh Ramakrishnan; Micah Goldblum; Colin White (NeurIPS, 2023)

Neural Architecture Search: Insights from 1000 Papers. - Colin White; Mahmoud Safari; Rhea Sukthanker; Binxin Ru; Thomas Elsken; Arber Zela; Debadeepta Dey; Frank Hutter (CoRR, 2023)

Speeding up Fourier Neural Operators via Mixed Precision. - Colin White; Renbo Tu; Jean Kossaifi; Gennady Pekhimenko; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2023)

Data Contamination Through the Lens of Time. - Manley Roberts; Himanshu Thakur; Christine Herlihy; Colin White; Samuel Dooley (CoRR, 2023)

Speeding up NAS with Adaptive Subset Selection. - Vishak Prasad C.; Colin White; Sibasis Nayak; Paarth Jain; Aziz Shameem; Prateek Garg; Ganesh Ramakrishnan (AutoML, 2024)

To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination. - Manley Roberts; Himanshu Thakur; Christine Herlihy; Colin White; Samuel Dooley (ICLR, 2024)

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators. - Renbo Tu; Colin White; Jean Kossaifi; Boris Bonev; Gennady Pekhimenko; Kamyar Azizzadenesheli; Anima Anandkumar (ICLR, 2024)

TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks. - Benjamin Feuer; Robin Schirrmeister; Valeriia Cherepanova; Chinmay Hegde; Frank Hutter; Micah Goldblum; Niv Cohen; Colin White (NeurIPS, 2024)

Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. - Md. Ashiqur Rahman; Robert Joseph George; Mogab Elleithy; Daniel V. Leibovici; Zongyi Li; Boris Bonev; Colin White; Julius Berner; Raymond A. Yeh; Jean Kossaifi; Kamyar Azizzadenesheli; Animashree Anandkumar (NeurIPS, 2024)

Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive. - Arka Pal; Deep Karkhanis; Samuel Dooley; Manley Roberts; Siddartha Naidu; Colin White (CoRR, 2024)

LiveBench: A Challenging, Contamination-Free LLM Benchmark. - Colin White; Samuel Dooley; Manley Roberts; Arka Pal; Benjamin Feuer; Siddhartha Jain 001; Ravid Shwartz-Ziv; Neel Jain; Khalid Saifullah; Siddartha Naidu; Chinmay Hegde; Yann LeCun; et al. (CoRR, 2024)

LiveBench: A Challenging, Contamination-Limited LLM Benchmark. - Colin White; Samuel Dooley; Manley Roberts; Arka Pal; Benjamin Feuer; Siddhartha Jain 001; Ravid Shwartz-Ziv; Neel Jain; Khalid Saifullah; Sreemanti Dey; Shubh-Agrawal; Sandeep Singh Sandha; et al. (ICLR, 2025)

Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes. - Mayuka Jayawardhana; Renbo Tu; Samuel Dooley; Valeriia Cherepanova; Andrew Gordon Wilson; Frank Hutter; Colin White; Tom Goldstein; Micah Goldblum (CoRR, 2025)

DSR-Bench: Evaluating the Structural Reasoning Abilities of LLMs via Data Structures. - Yu He; Yingxi Li; Colin White; Ellen Vitercik (CoRR, 2025)