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09/19/2023
Accelerating Diffusion-Based Text-to-Audio Generation with Consistency Distillation
Diffusion models power a vast majority of text-to-audio (TTA) generation...
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07/29/2023
Initial State Interventions for Deconfounded Imitation Learning
Imitation learning suffers from causal confusion. This phenomenon occurs...
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03/29/2023
Meta-Learning Parameterized First-Order Optimizers using Differentiable Convex Optimization
Conventional optimization methods in machine learning and controls rely ...
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02/15/2023
Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points
This paper studies the role of over-parametrization in solving non-conve...
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02/03/2023
Asymmetric Certified Robustness via Feature-Convex Neural Networks
Recent works have introduced input-convex neural networks (ICNNs) as lea...
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01/29/2023
Improving the Accuracy-Robustness Trade-off of Classifiers via Adaptive Smoothing
While it is shown in the literature that simultaneously accurate and rob...
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01/04/2023
Cost Inference for Feedback Dynamic Games from Noisy Partial State Observations and Incomplete Trajectories
In multi-agent dynamic games, the Nash equilibrium state trajectory of e...
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08/15/2022
Semidefinite Programming versus Burer-Monteiro Factorization for Matrix Sensing
Many fundamental low-rank optimization problems, such as matrix completi...
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08/15/2022
An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models
In this discussion paper, we survey recent research surrounding robustne...
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03/18/2022
Infinite-Horizon Reach-Avoid Zero-Sum Games via Deep Reinforcement Learning
In this paper, we consider the infinite-horizon reach-avoid zero-sum gam...
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03/08/2022
Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate
This paper is concerned with low-rank matrix optimization, which has fou...
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01/06/2022
Efficient Global Optimization of Two-layer ReLU Networks: Quadratic-time Algorithms and Adversarial Training
The non-convexity of the artificial neural network (ANN) training landsc...
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12/27/2021
Safe Reinforcement Learning with Chance-constrained Model Predictive Control
Real-world reinforcement learning (RL) problems often demand that agents...
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10/19/2021
Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient Methods
It is well-known that the Burer-Monteiro (B-M) factorization approach ca...
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05/31/2021
Node-Variant Graph Filters in Graph Neural Networks
Graph neural networks (GNNs) have been successfully employed in a myriad...
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05/25/2021
Practical Convex Formulation of Robust One-hidden-layer Neural Network Training
Recent work has shown that the training of a one-hidden-layer, scalar-ou...
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05/18/2021
Sharp Restricted Isometry Property Bounds for Low-rank Matrix Recovery Problems with Corrupted Measurements
In this paper, we study a general low-rank matrix recovery problem with ...
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01/22/2021
Partition-Based Convex Relaxations for Certifying the Robustness of ReLU Neural Networks
In this paper, we study certifying the robustness of ReLU neural network...
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12/07/2020
Improving Fairness and Privacy in Selection Problems
Supervised learning models have been increasingly used for making decisi...
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10/16/2020
Strengthened SDP Verification of Neural Network Robustness via Non-Convex Cuts
There have been major advances on the design of neural networks, but sti...
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10/15/2020
Certifying Neural Network Robustness to Random Input Noise from Samples
Methods to certify the robustness of neural networks in the presence of ...
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10/02/2020
Data-Driven Assessment of Deep Neural Networks with Random Input Uncertainty
When using deep neural networks to operate safety-critical systems, asse...
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09/14/2020
Implicit Graph Neural Networks
Graph Neural Networks (GNNs) are widely used deep learning models that l...
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04/01/2020
Tightened Convex Relaxations for Neural Network Robustness Certification
In this paper, we consider the problem of certifying the robustness of n...
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03/16/2020
Spectral Graph Attention Network
Variants of Graph Neural Networks (GNNs) for representation learning hav...
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09/21/2019
Efficient Learning of Distributed Linear-Quadratic Controllers
In this work, we propose a robust approach to design distributed control...
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08/04/2019
Boundary Defense against Cyber Threat for Power System Operation
The operation of power grids is becoming increasingly data-centric. Whil...
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07/09/2019
Global Optimality Guarantees for Nonconvex Unsupervised Video Segmentation
In this paper, we consider the problem of unsupervised video object segm...
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05/24/2019
Power up! Robust Graph Convolutional Network against Evasion Attacks based on Graph Powering
Graph convolutional networks (GCNs) are powerful tools for graph-structu...
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04/20/2019
Learning Sparse Dynamical Systems from a Single Sample Trajectory
This paper addresses the problem of identifying sparse linear time-invar...
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01/07/2019
Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery
Nonconvex matrix recovery is known to contain no spurious local minima u...
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12/30/2018
Exact Guarantees on the Absence of Spurious Local Minima for Non-negative Robust Principal Component Analysis
This work is concerned with the non-negative robust principal component ...
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09/16/2018
A Fog Robotic System for Dynamic Visual Servoing
Cloud Robotics is a paradigm where distributed robots are connected to c...
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05/25/2018
How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?
When the linear measurements of an instance of low-rank matrix recovery ...
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03/21/2018
Data-Driven Sparse System Identification
In this paper, we study the system identification porblem for sparse lin...
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02/14/2018
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
The sparse inverse covariance estimation problem is commonly solved usin...
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02/14/2018
Linear-Time Algorithm for Learning Large-Scale Sparse Graphical Models
The sparse inverse covariance estimation problem is commonly solved usin...
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11/24/2017
Sparse Inverse Covariance Estimation for Chordal Structures
In this paper, we consider the Graphical Lasso (GL), a popular optimizat...
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08/30/2017
