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Abstract: The stochastic inventory control problem under censored demands is a fundamental problem in revenue and supply chain management. A simple class of policies…
Learning in structured MDPs with convex cost…
From Oluwasanmi Koyejo
16 plays 0 -
Abstract: Policy gradient methods apply to complex, poorly understood, control problems by performing stochastic gradient descent over a parameterized class of…
On the Global Convergence and Approximation…
From Oluwasanmi Koyejo
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Abstract: Recent investigations into infinitely-wide deep neural networks have given rise to intriguing connections between deep networks, kernel methods, and Gaussian…
A Phase Transition in Gradient Descent for Wide,…
From Oluwasanmi Koyejo
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Abstract: Does deep learning actually need to be deep? In this talk, I will present some of our recent and ongoing work on Deep Equilibrium (DEQ) Models, an approach…
Equilibrium approaches to deep learning: One…
From Oluwasanmi Koyejo
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Abstract: We study the problem of recovering a planted matching in randomly weighted complete bipartite graphs with n nodes. For some unknown perfect matching M*, the…
Planted Matching Problem, Mehrdad Moharrami; IDS2…
From Oluwasanmi Koyejo
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Abstract: In numerous decision-making processes such as algorithm portfolio design and adaptive routing, each action incurs a random cost and yields a random and…
Budget-Constrained Learning and Optimization with…
From Oluwasanmi Koyejo
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Abstract: Modern Reinforcement Learning (RL) is commonly applied to practical problems with an enormous number of states, where function approximation such as deep…
Provably Efficient Exploration in Reinforcement…
From Oluwasanmi Koyejo
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Abstract: Flexible, yet interpretable, models for the second-order temporal structure are needed in scientific analyses of high-dimensional data. We develop a…
A Nonconvex Framework for Structured Dynamic…
From Oluwasanmi Koyejo
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Byzantine Tolerance for Distributed SGD; Cong Xie, IDS2 seminar series
Byzantine Tolerance for Distributed SGD; Cong…
From Oluwasanmi Koyejo
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Abstract: How does a 110-layer ResNet learn a high-complexity classifier using relatively few training examples and short training time? We present a theory towards…
Backward feature correction: How can deep…
From Oluwasanmi Koyejo
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Abstract: System identification has a long history with several well-established methods, in particular for learning linear dynamical systems from input/output data.…
A fresh look at a classical system identification…
From Oluwasanmi Koyejo
10 plays 0
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