Yang Cai

Professor of Computer Science and Economics at Yale University

[Yang Cai @Yang_Cai]

Our paper “What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness” received the Best Paper Award at COLT 2025!

Huge shout-out to my amazing collaborators: Alkis Kalavasis, Katerina Mamali, @AnayMehrotra, and Manolis Zampetakis.

[Yang Cai @Yang_Cai]

Anay and Alkis are on the job market this year—keep an eye out!

📄 Paper: https://t.co/NDv4Jl1wgH

[Yang Cai @Yang_Cai]

Our paper “What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness” received the Best Paper Award at COLT 2025!

Huge shout-out to my amazing collaborators: Alkis Kalavasis, Katerina Mamali, @AnayMehrotra, and Manolis Zampetakis.

[Yale Computer Science @YaleCSDept]

We're hiring in CS!
Associate/full professor level in AI & NLP:
https://t.co/DgquxY0VgS
Assistant professor level in databases & data management:
https://t.co/yqmxMK0c6K

[Yang Cai @Yang_Cai]

@ProfJeffBrock Thanks, Jeff!

[Yang Cai @Yang_Cai]

Our proof builds on a new natural potential function, whose monotonicity is established using a sum-of-squares programming based computer-aided proof.

For more details, see my talk at the Simons Institute for our result on EG.
https://t.co/eMr8KJmdtT

[Yang Cai @Yang_Cai]

Very excited about our new paper with @ArgyrisOikonom1 @WeiqiangZheng3.

We obtain the tight last-iterate convergence rates for the Extragradient (EG) and Optimistic Gradient (OG) algorithms, settling an open problem raised by @KonstDaskalakis.
https://t.co/oBMy8THcVu

[Yang Cai @Yang_Cai]

For both EG and OG, we know that the last-iterate asymptotically converges, but the rate was not known despite having been studied for a long time. We obtain tight last-iterate convergence rates for both EG and OG.

[TCS blog aggregator @cstheory]

Anti-Complexitism « Shtetl-Optimized: http://bit.ly/cvMKeR