Guy Blanc

Contact: gblanc (at) stanford.edu

guy_head_shot 

I'm Guy, a fourth year PhD student in the Stanford CS theory group. I am extremely fortunate to be advised by Li-Yang Tan.

In my free time, I enjoy hiking, dancing, and playing/watching sports.

Papers

In my field, we generally order authors alphabetically by last name.

A Strong Composition Theorem for Junta Complexity and the Boosting of Property Testers

Guy Blanc, Caleb Koch, Carmen Strassle, and Li-Yang Tan
FOCS 2023

Harnessing the Power of Choices in Decision Tree Learning

Guy Blanc, Jane Lange, Chirag Pabbaraju, Colin Sullivan, Li-Yang Tan, and Mo Tiwari
NeurIPS 2023

Subsampling Suffices for Adaptive Data Analysis

Guy Blanc
STOC 2023
Best student paper at STOC 2023
Invited to STOC 2023 special issue

Lifting uniform learners via distributional decomposition

Guy Blanc, Jane Lange, Ali Malik, and Li-Yang Tan
STOC 2023

Multitask Learning via Shared Features: Algorithms and Hardness

Konstantina Bairaktari, Guy Blanc, Li-Yang Tan, Jonathan Ullman, Lydia Zakynthinou
COLT 2023

Certification with an NP Oracle

Guy Blanc, Caleb Koch, Jane Lange, Carmen Strassle, and Li-Yang Tan
ITCS 2023

A query-optimal algorithm for finding counterfactuals

Guy Blanc, Caleb Koch, Jane Lange, and Li-Yang Tan
ICML 2022

Popular decision tree algorithms are provably noise tolerant

Guy Blanc, Jane Lange, Ali Malik, and Li-Yang Tan
ICML 2022

On the power of adaptivity in statistical adversaries

Guy Blanc, Jane Lange, Ali Malik, and Li-Yang Tan
COLT 2022

Open problem: Properly learning decision trees in polynomial time?

Guy Blanc, Jane Lange, Mingda Qiao, and Li-Yang Tan
COLT 2022
Open problems track

New Near-Linear Time Decodable Codes Closer to the GV Bound

Guy Blanc and Dean Doron
CCC 2022

Reconstructing decision trees

Guy Blanc, Jane Lange, and Li-Yang Tan
ICALP 2022

The query complexity of certification

Guy Blanc, Caleb Koch, Jane Lange, and Li-Yang Tan
STOC 2022

Provably efficient, succinct, and precise explanations

Guy Blanc, Jane Lange, and Li-Yang Tan
NeurIPS 2021

Multiway online correlated selection

Guy Blanc and Moses Charikar
FOCS 2021

Properly learning decision trees in almost polynomial time

Guy Blanc, Jane Lange, Mingda Qiao, and Li-Yang Tan
FOCS 2021
Invited to FOCS 2021 special issue
Journal of the ACM

Decision tree heuristics can fail, even in the smoothed setting

Guy Blanc, Jane Lange, Mingda Qiao, and Li-Yang Tan
RANDOM 2021

Learning stochastic decision trees

Guy Blanc, Jane Lange, and Li-Yang Tan
ICALP 2021

Query strategies for priced information, revisited

Guy Blanc, Jane Lange, and Li-Yang Tan
SODA 2021

Universal guarantees for decision tree induction via a higher-order splitting criterion

Guy Blanc, Neha Gupta, Jane Lange, and Li-Yang Tan
NeurIPS 2020

Estimating decision tree learnability with polylogarithmic sample complexity

Guy Blanc, Neha Gupta, Jane Lange, and Li-Yang Tan
NeurIPS 2020

Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process

Guy Blanc, Neha Gupta, Gregory Valiant, and Paul Valiant
COLT 2020

Provable guarantees for decision tree induction: the agnostic setting

Guy Blanc, Jane Lange, and Li-Yang Tan
ICML 2020

Top-down induction of decision trees: rigorous guarantees and inherent limitations

Guy Blanc, Jane Lange, and Li-Yang Tan
ITCS 2020

Adaptive sampled softmax with kernel based sampling

Guy Blanc, Steffen Rendle
ICML 2018