research
∙
02/19/2023
Noise-Augmented ℓ_0 Regularization of Tensor Regression with Tucker Decomposition
Tensor data are multi-dimension arrays. Low-rank decomposition-based reg...
share
research
∙
12/26/2022
On linear-algebraic notions of expansion
A fundamental fact about bounded-degree graph expanders is that three no...
research
∙
07/16/2022
Clover: Towards A Unified Video-Language Alignment and Fusion Model
Building a universal video-language model for solving various video unde...
research
∙
06/09/2022
Connections between graphs and matrix spaces
Given a bipartite graph G, the graphical matrix space 𝒮_G consists of ma...
research
∙
04/18/2022
Adaptive Noisy Data Augmentation for Regularized Estimation and Inference in Generalized Linear Models
We propose the AdaPtive Noise Augmentation (PANDA) procedure to regulari...
research
∙
10/16/2021
Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling
We propose Noise-Augmented Privacy-Preserving Empirical Risk Minimizatio...
research
∙
07/06/2021
On a tracial version of Haemers bound
We extend upper bounds on the quantum independence number and the quantu...
research
∙
02/10/2021
Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov noise
We develop a computationally-efficient PAC active learning algorithm for...
research
∙
11/25/2020
Quantum algorithms for matrix scaling and matrix balancing
Matrix scaling and matrix balancing are two basic linear-algebraic probl...
research
∙
08/27/2020
Interior-point methods for unconstrained geometric programming and scaling problems
We provide a condition-based analysis of two interior-point methods for ...
research
∙
04/22/2020
Qd-tree: Learning Data Layouts for Big Data Analytics
Corporations today collect data at an unprecedented and accelerating sca...
research
∙
04/02/2020
Continuous Motion Planning with Temporal Logic Specifications using Deep Neural Networks
In this paper, we propose a model-free reinforcement learning method to ...
research
∙
07/12/2019
A Quantum-inspired Classical Algorithm for Separable Non-negative Matrix Factorization
Non-negative Matrix Factorization (NMF) asks to decompose a (entry-wise)...
research
∙
06/18/2019
Fast Converging and Robust Optimal Path Selection in Continuous-time Markov-switching GARCH Model
We propose CROPS, a fast Converging and Robust Optimal Path Selection al...
research
∙
05/21/2019
ALEX: An Updatable Adaptive Learned Index
Recent work on "learned indexes" has revolutionized the way we look at t...
research
∙
05/06/2019
Incorporating Weisfeiler-Leman into algorithms for group isomorphism
In this paper we combine many of the standard and more recent algebraic ...
research
∙
11/11/2018
Reactive Task and Motion Planning for Robust Whole-Body Dynamic Locomotion in Constrained Environments
Contact-based decision and planning methods are becoming increasingly im...
research
∙
10/19/2018
AdaPtive Noisy Data Augmentation (PANDA) for Simultaneous Construction Multiple Graph Models
We extend the data augmentation technique (PANDA) by Li et al. (2018) fo...
research
∙
10/11/2018
Panda: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models
We propose PANDA, an AdaPtive Noise Augmentation technique to regularize...
research
∙
10/01/2018
Quantum asymptotic spectra of graphs and non-commutative graphs, and quantum Shannon capacities
We study several quantum versions of the Shannon capacity of graphs and ...
research
∙
10/26/2017
