Kamalika Chaudhuri
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no series more than once — all 6 in the filters
on a stage with
- Adria Gascononce
- Chhavi Yadavonce
- Dan Ramageonce
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| title | conference | date |
|---|---|---|
| Opening Remarks | Federated and Collaborative Learning Boot Camp 2026 | 2026-01-26 |
Program states a semester-long Simons initiative with a bootcamp this week plus workshops in February March and April on heterogeneous sources, trust and… | ||
| Talk by Kamalika Chaudhuri (Meta) | Federated and Collaborative Learning Boot Camp 2026 | 2026-01-26 |
Built a controllable web-agent testbed and AgentDAM benchmark that runs multi-step UI tasks on synthetic user data and memory profiles, measures two… | ||
| Panel Discussion | Domain Adaptation and Related Areas 2024 | 2024-11-12 |
Panelists debate whether scaling plus architecture wins: larger pretrained models (CLIP/LLMs) empirically fix many classic domain-adaptation traps (e.g… | ||
| TBD | Domain Adaptation and Related Areas 2024 | 2024-11-12 |
Proposes a statistical IRM scaffold: three concrete conditions—source-preservation, contraction, Bayes-unifies—and proves that with an oracle representation… | ||
| Nearest Neighbors I | Deep Learning Boot Camp 2019 | 2019-05-28 |
K‑nearest neighbors is universally consistent when K → ∞ and K/N → 0, and regression rates scale like N^{-2/(2+D)} with the optimal K ≈ N^{2/(2+D)}, exposing… | ||
| Nearest Neighbors II | Deep Learning Boot Camp 2019 | 2019-05-28 |
One nearest neighbor has robustness radius → 0 at points where mu is continuous and eta(x)∈(0,1) so accuracy can remain high while robustness vanishes as n→∞… | ||
| Beyond Worst Case: When Complex Feedback Can Improve the Label Complexity of Active Learning | Learning, Algorithm Design and Beyond Worst-Case Analysis | 2016-11-14 |
Combines a cheap but biased weak labeler and an expensive correct oracle by training a cost-sensitive difference classifier that enforces very low false… | ||
| Pufferfish Privacy Mechanisms for Correlated Data | Uncertainty in Computation 2016 | 2016-10-04 |
Proposes a concrete privacy framework for correlated data and two mechanisms: the Wasserstein mechanism uses the infinity-Wasserstein distance as an analog of… | ||
| Confidence-Based Active Learning | Information Theory, Learning and Big Data (Simons Institute, 2015) | 2015-03-16 |
Presents a reduction from agnostic active learning to a confidence-rated predictor with nonzero error guarantee and gives an LP to construct that predictor… | ||
| nothing matches | ||