John C. Duchi
35 papers · 2006–2024 · 5 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 9 separate collaboration groups - the largest holds only 40% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which John C. Duchi?
4 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Yair Carmon, Hilal Asi, Daniel Levy
14 papers
· 2017–2024
· NeurIPS, COLT, AISTATS
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Universally Instance-Optimal Mechanisms for Private Statistical Estimation
COLT 2024
Collaboratively Learning Linear Models with Structured Missing Data
NeurIPS 2023
Adapting to function difficulty and growth conditions in private optimization
NeurIPS 2021
Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices
NeurIPS 2020
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms
NeurIPS 2020
Large-Scale Methods for Distributionally Robust Optimization
NeurIPS 2020
Minibatch Stochastic Approximate Proximal Point Methods
NeurIPS 2020
Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations
COLT 2020
Modeling simple structures and geometry for better stochastic optimization algorithms
AISTATS 2019
Necessary and Sufficient Geometries for Gradient Methods
NeurIPS 2019
Unlabeled Data Improves Adversarial Robustness
NeurIPS 2019
Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems
NeurIPS 2018
Unsupervised Transformation Learning via Convex Relaxations
NeurIPS 2017
“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions
ICML 2017
5 papers whose co-authors appear nowhere else under this name
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise
NeurIPS 2022
Local Minimax Complexity of Stochastic Convex Optimization
NeurIPS 2016
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care
NeurIPS 2015
Efficient Learning using Forward-Backward Splitting
NeurIPS 2009
Using Combinatorial Optimization within Max-Product Belief Propagation
NeurIPS 2006