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03/27/2023
Finite Strain Topology Optimization with Nonlinear Stability Constraints
This paper proposes a computational framework for the design optimizatio...
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02/20/2023
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation
Skip connections and normalisation layers form two standard architectura...
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01/18/2023
Understand Code Style: Efficient CNN-based Compiler Optimization Recognition System
Compiler optimization level recognition can be applied to vulnerability ...
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03/15/2022
Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers
Training very deep neural networks is still an extremely challenging tas...
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11/03/2021
On the Application of Data-Driven Deep Neural Networks in Linear and Nonlinear Structural Dynamics
The use of deep neural network (DNN) models as surrogates for linear and...
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08/27/2021
Learning to Give Checkable Answers with Prover-Verifier Games
Our ability to know when to trust the decisions made by machine learning...
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07/21/2021
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise
Annealed importance sampling (AIS) and related algorithms are highly eff...
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06/10/2021
A Central Limit Theorem, Loss Aversion and Multi-Armed Bandits
This paper establishes a central limit theorem under the assumption that...
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02/18/2021
Don't Fix What ain't Broke: Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization
Minimax optimization has recently gained a lot of attention as adversari...
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10/05/2020
Computational frameworks for homogenization and multiscale stability analyses of nonlinear periodic metamaterials
This paper presents a consistent computational framework for multiscale ...
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09/23/2020
A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints
The theory of integral quadratic constraints (IQCs) allows the certifica...
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08/17/2020
On the Suboptimality of Negative Momentum for Minimax Optimization
Smooth game optimization has recently attracted great interest in machin...
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02/18/2020
Picking Winning Tickets Before Training by Preserving Gradient Flow
Overparameterization has been shown to benefit both the optimization and...
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10/16/2019
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
Many tasks in modern machine learning can be formulated as finding equil...
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07/09/2019
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
Increasing the batch size is a popular way to speed up neural network tr...
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07/03/2019
Benchmarking Model-Based Reinforcement Learning
Model-based reinforcement learning (MBRL) is widely seen as having the p...
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05/27/2019
Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks
Natural gradient descent has proven effective at mitigating the effects ...
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05/15/2019
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
Reducing the test time resource requirements of a neural network while p...
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04/25/2019
Computational Design of Finite Strain Auxetic Metamaterials via Topology Optimization and Nonlinear Homogenization
A novel computational framework for designing metamaterials with negativ...
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03/14/2019
Functional Variational Bayesian Neural Networks
Variational Bayesian neural networks (BNNs) perform variational inferenc...
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02/21/2019
Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise
The choice of batch-size in a stochastic optimization algorithm plays a ...
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11/30/2018
Eigenvalue Corrected Noisy Natural Gradient
Variational Bayesian neural networks combine the flexibility of deep lea...
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10/29/2018
Three Mechanisms of Weight Decay Regularization
Weight decay is one of the standard tricks in the neural network toolbox...
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06/12/2018
Differentiable Compositional Kernel Learning for Gaussian Processes
The generalization properties of Gaussian processes depend heavily on th...
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12/06/2017
Noisy Natural Gradient as Variational Inference
Combining the flexibility of deep learning with Bayesian uncertainty est...
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03/17/2017
