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Felix Zhou

@felix-zhou-cfz.bsky.social
30 followers 106 following 12 posts

PhD student @Yale studying Algorithms and Machine Learning felix-zhou.com

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Felix Zhou @felix-zhou-cfz.bsky.social · 30/05/2026
Karan and Du, followed by @haithambouammar.bsky.social et al., showed that inference-time sampling from carefully chosen distributions improves LLM reasoning; no posttraining, reward curation, or verifier needed. We show smarter test-time budget allocation yields drastic gains! (1/3)
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Reposted by Felix Zhou
Gautam Kamath @gautamkamath.com · 03/02/2026
Do you have recent work on differential privacy? Submit it to TPDP 2026 in Boston, whose deadline is in ~2 weeks. TPDP is a lightly reviewed workshop, whose main purpose is getting researchers in DP together in one place. Dual submissions allowed (and encouraged!).
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Reposted by Felix Zhou
anaymehrotra.bsky.social @anaymehrotra.bsky.social · 30/11/2025
Our #NeurIPS2025 workshop “Reliable ML from Unreliable Data” schedule is live! 🎉 Talks, posters, and a panel all day, plus a best paper session (announcement coming soon 👀). Come hang out with us for the full program!
A black and white illustration of a scroll-style banner containing the text "RELIABLE ML WORKSHOP at NeurIPS'25"
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Felix Zhou @felix-zhou-cfz.bsky.social · 18/10/2025
Previous densest subgraph algorithms in the continual release model incur O(log n) error and space overhead compared to static counterparts. By densifying the input graph, this overhead can be removed! To appear in SOSA'26.
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Felix Zhou @felix-zhou-cfz.bsky.social · 19/04/2025
"What makes a good fisherman as opposed to other professions?" This question can be formulated as a k-linear regression problem with self-selection bias. Alkis, @anaymehrotra.bsky.social, and I design faster local convergence algorithms for this problem: arxiv.org/abs/2504.07133 (1/7)
arxiv.org
Can SGD Select Good Fishermen? Local Convergence under Self-Selection Biases and Beyond
We revisit the problem of estimating $k$ linear regressors with self-selection bias in $d$ dimensions with the maximum selection criterion, as introduced by Cherapanamjeri, Daskalakis, Ilyas, and Zamp...
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