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09/19/2023
PanopticNeRF-360: Panoramic 3D-to-2D Label Transfer in Urban Scenes
Training perception systems for self-driving cars requires substantial a...
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06/05/2023
Deep Learning From Crowdsourced Labels: Coupled Cross-entropy Minimization, Identifiability, and Regularization
Using noisy crowdsourced labels from multiple annotators, a deep learnin...
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06/05/2023
Under-Counted Tensor Completion with Neural Incorporation of Attributes
Systematic under-counting effects are observed in data collected across ...
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05/30/2023
Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach
The recent integration of deep learning and pairwise similarity annotati...
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03/03/2023
Quantized Radio Map Estimation Using Tensor and Deep Generative Models
Spectrum cartography (SC), also known as radio map estimation (RME), aim...
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01/18/2023
OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generation
Recent advances in modeling 3D objects mostly rely on synthetic datasets...
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10/14/2022
Provable Subspace Identification Under Post-Nonlinear Mixtures
Unsupervised mixture learning (UML) aims at identifying linearly or nonl...
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09/26/2022
HSD: A hierarchical singing annotation dataset
Commonly music has an obvious hierarchical structure, especially for the...
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08/05/2022
A Noise-Robust Loss for Unlabeled Entity Problem in Named Entity Recognition
Named Entity Recognition (NER) is an important task in natural language ...
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06/14/2022
On Finite-Sample Identifiability of Contrastive Learning-Based Nonlinear Independent Component Analysis
Nonlinear independent component analysis (nICA) aims at recovering stati...
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06/11/2022
Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Machine Learning
This work revisits the joint beamforming (BF) and antenna selection (AS)...
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05/08/2022
Fast and Structured Block-Term Tensor Decomposition For Hyperspectral Unmixing
The block-term tensor decomposition model with multilinear rank-(L_r,L_r...
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03/29/2022
Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation
Large-scale training data with high-quality annotations is critical for ...
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12/31/2021
Uncovering migration systems through spatio-temporal tensor co-clustering
A central problem in the study of human mobility is that of migration sy...
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09/25/2021
Communication-Efficient Distributed Linear and Deep Generalized Canonical Correlation Analysis
Classic and deep learning-based generalized canonical correlation analys...
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09/23/2021
Memory-Efficient Convex Optimization for Self-Dictionary Separable Nonnegative Matrix Factorization: A Frank-Wolfe Approach
Nonnegative matrix factorization (NMF) often relies on the separability ...
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06/16/2021
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder
This work focuses on the problem of unraveling nonlinearly mixed latent ...
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06/14/2021
Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization
Unsupervised learning of the Dawid-Skene (D S) model from noisy, incom...
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06/14/2021
Latent Correlation-Based Multiview Learning and Self-Supervision: A Unifying Perspective
Multiple views of data, both naturally acquired (e.g., image and audio) ...
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05/03/2021
Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspective
There has been a growing interest in developing data-driven, and in part...
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05/01/2021
Stochastic Block-ADMM for Training Deep Networks
In this paper, we propose Stochastic Block-ADMM as an approach to train ...
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05/01/2021
Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models
The spectrum cartography (SC) technique constructs multi-domain (e.g., f...
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04/29/2021
Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses
This work considers low-rank canonical polyadic decomposition (CPD) unde...
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02/24/2021
Hyperspectral Denoising Using Unsupervised Disentangled Spatio-Spectral Deep Priors
Image denoising is often empowered by accurate prior information. In rec...
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02/17/2021
StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling
This paper focuses on a core task in computational sustainability and st...
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01/11/2021
A More Efficient Chinese Named Entity Recognition base on BERT and Syntactic Analysis
We propose a new Named entity recognition (NER) method to effectively ma...
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11/25/2020
Mixed Membership Graph Clustering via Systematic Edge Query
This work considers clustering nodes of a largely incomplete graph. Unde...
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11/16/2020
Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment
There has been a growing interest in developing data-driven and in parti...
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06/30/2020
Recovering Joint Probability of Discrete Random Variables from Pairwise Marginals
Learning the joint probability of random variables (RVs) lies at the hea...
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06/15/2020
Nonconvex Optimization Tools for Large-Scale Matrix and Tensor Decomposition with Structured Factors
The proposed article aims at offering a comprehensive tutorial for the c...
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01/08/2020
On Recoverability of Randomly Compressed Tensors with Low CP Rank
Our interest lies in the recoverability properties of compressed tensors...
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09/26/2019
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms
The data deluge comes with high demands for data labeling. Crowdsourcing...
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09/19/2019
Neural Network-Assisted Nonlinear Multiview Component Analysis: Identifiability and Algorithm
Multiview analysis aims at extracting shared latent components from data...
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07/02/2019
Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix Estimation
Hyperspectral super-resolution (HSR) is a problem that aims to estimate ...
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02/02/2019
Multiuser Video Streaming Rate Adaptation: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach
We consider a multi-user video streaming service optimization problem ov...
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01/16/2019
Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization
This work considers the problem of computing the canonical polyadic deco...
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01/06/2019
Learning Nonlinear Mixtures: Identifiability and Algorithm
Linear mixture models have proven very useful in a plethora of applicati...
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04/24/2018
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data
The sum-of-correlations (SUMCOR) formulation of generalized canonical co...
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04/05/2018
Timing Channel in IaaS: How to Identify and Investigate
Recently, the IaaS (Infrastructure as a Service) Cloud (e.g., Amazon EC2...
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03/03/2018
Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications
Nonnegative matrix factorization (NMF) has become a workhorse for signal...
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02/19/2018
Learning Hidden Markov Models from Pairwise Co-occurrences with Applications to Topic Modeling
We present a new algorithm for identifying the transition and emission p...
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12/29/2017
Limited Feedback Channel Estimation in Massive MIMO with Non-uniform Directional Dictionaries
Channel state information (CSI) at the base station (BS) is crucial to a...
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12/13/2017
Penalty Dual Decomposition Method For Nonsmooth Nonconvex Optimization
Many contemporary signal processing, machine learning and wireless commu...
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12/01/2017
Tensors, Learning, and 'Kolmogorov Extension' for Finite-alphabet Random Vectors
Estimating the joint probability mass function (PMF) of a set of random ...
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11/20/2017
On Convergence of Epanechnikov Mean Shift
Epanechnikov Mean Shift is a simple yet empirically very effective algor...
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09/02/2017
On Identifiability of Nonnegative Matrix Factorization
In this letter, we propose a new identification criterion that guarantee...
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11/15/2016
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm
In topic modeling, many algorithms that guarantee identifiability of the...
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08/15/2016
Robust Volume Minimization-Based Matrix Factorization for Remote Sensing and Document Clustering
This paper considers volume minimization (VolMin)-based structured matri...
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07/06/2016
Tensor Decomposition for Signal Processing and Machine Learning
Tensors or multi-way arrays are functions of three or more indices (i,j...
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05/31/2016