Meetings/Workshops on Mathematical Logic and Foundations in the United States (USA)

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1
Advances and Challenges in Hyperbolic Conservation Laws
17 May 2021 - 21 May 2021 • Providence, RI, United States
Organizer:
ICERM
Abstract:
In the field of hyperbolic conservation laws, theory, computation, and applications are deeply connected, with each one providing to the other two technical support as well as insights. Major progress has been achieved, over the past 40 years, on the theory and computation of solutions in one space dimension. By contrast, the multi-space dimensional case is still covered by mist, which is now gradually lifting, revealing new vistas. For instance, in two space dimensions, significant progress has been achieved in the study of transonic gas flow, of central importance to aerodynamics. Parallel progress has been reported on the numerical side, with the design of high-order accurate discontinuous Galerkin and finite volume computational schemes, even for multidimensional systems. Finally, we are witnessing an explosion in the applications, not only on the traditional turf of fluid dynamics but also in new directions, in materials science, biology, traffic theory, etc.
Contact:
Phone: [401 863 5030];     Email: info@icerm.brown.edu
Event listing ID:
1384172
2
BLAST 2021
09 Jun 2021 - 13 Jun 2021 • Las Cruces, NM – online, United States
Organizer:
New Mexico State University, Las Cruces, NM
Abstract:
BLAST is a conference series focusing on Boolean Algebras Lattices, Algebraic and Quantum logic Universal Algebra Set Theory Set-theoretic and Point-free Topology
Event listing ID:
1402886
Related subject(s):
3
Workshop on Advances in Theory and Algorithms for Deep Reinforcement Learning
02 Aug 2021 - 04 Aug 2021 • Providence, RI, United States
Organizer:
ICERM
Abstract:
There has been significant progress over the last few years in the theory and applications of Reinforcement Learning (RL). While RL theory and applications have had a rich history going back several decades, the major recent successes have occurred due to a successful marriage between deep learning approaches for function approximation embedded within a reinforcement learning framework for decision-making (Deep RL). On one hand, there has been a richer understanding of Stochastic Gradient Descent (SGD) for non-convex optimization, its impact in driving training error to zero in deep neural networks, and on the generalization ability of such networks for inference. On the other hand, there has been an explosion of research on iterative learning algorithms with strong statistical guarantees in the settings of reinforcement learning, stochastic approximation and multi-armed bandits. This workshop aims to bring leading researchers from these two threads, with the goal of understanding and advancing research at their intersection. We will also explore other potential connections between deep learning and deep RL, including but not limited to: Understanding generalization in deep RL and how it is related to and/or different from generalization in deep learning; Connections between adversarial training in deep learning (e.g., Generative Adversarial Networks) and the optimization aspects of recent deep RL algorithms based on generalized moment matching in off-policy RL and imitation learning. This workshop is fully funded by a Simons Foundation Targeted Grant to Institutes.
Contact:
Email: info@icerm.brown.edu
Event listing ID:
1414851


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Last updated: 17 March 2021