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ORCID31st MLSP 2021: Gold Coast, Australia
- 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), Gold Coast, Australia, October 25-28, 2021. IEEE 2021, ISBN 978-1-7281-6338-3
- Ladislav Rampásek, Guy Wolf:
Hierarchical Graph Neural Nets can Capture Long-Range Interactions. 1-6 - Nathanaël Carraz Rakotonirina:
Self-Attention for Audio Super-Resolution. 1-6 - Femke B. Gelderblom, Tor André Myrvoll:
Deep Complex Convolutional Recurrent Network for Multi-Channel Speech Enhancement and Dereverberation. 1-6 - Akira Tanaka, Masanari Nakamura, Hideyuki Imai:
Model Selection of Kernel Ridge Regression for Extrapolation. 1-6 - Heitor R. Guimarães
, Wesley Beccaro, Miguel Arjona Ramírez:
Optimizing Time Domain Fully Convolutional Networks for 3D Speech Enhancement in a Reverberant Environment Using Perceptual Losses. 1-6 - Yitian Chen, Hamed Nosrati, Elias Aboutanios:
Online DOA Estimation for Noninteger Linear Antenna Arrays in Coarray Domain. 1-6 - Emilio Ruiz-Moreno, Baltasar Beferull-Lozano:
Tracking of Quantized Signals Based on Online Kernel Regression. 1-6 - Hyuntak Lim, Si-Dong Roh, Sangki Park, Ki-Seok Chung:
Robustness-Aware Filter Pruning for Robust Neural Networks Against Adversarial Attacks. 1-6 - Morten Østergaard Nielsen, Jan Østergaard, Jesper Jensen, Zheng-Hua Tan:
Compression of DNNs Using Magnitude Pruning and Nonlinear Information Bottleneck Training. 1-6 - Xusheng Wang, Mingtao Pei, Zhengang Nie:
Self-Trained Video Anomaly Detection Based on Teacher-Student Model. 1-6 - Diego Stucchi, Andrea Corsini, Goëry Genty, Giacomo Boracchi, Alessandro Foi:
A Weighted Loss Function to Predict Control Parameters for Supercontinuum Generation Via Neural Networks. 1-6 - Trevor C. Vannoy, Trey P. Scofield, Joseph A. Shaw, Riley D. Logan, Bradley M. Whitaker, Elizabeth M. Rehbein:
Detection of Insects in Class-Imbalanced Lidar Field Measurements. 1-6 - Angelos Nalmpantis, Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas:
Improving Deep Reinforcement Learning for Financial Trading Using Deep Adaptive Group-Based Normalization. 1-6 - Shivani Yadav, Dipanjan Gope, Uma Maheswari Krishnaswamy, Prasanta Kumar Ghosh:
Convolutional Dense Neural Network Based Spirometry Variable FVC Prediction Using Sustained Phonations. 1-6 - Tomer Weiss, Nissim Peretz, Sanketh Vedula, Arie Feuer, Alexander M. Bronstein:
Joint Optimization of System Design and Reconstruction in MIMO Radar Imaging. 1-6 - Alexander Tong, Frederick Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf:
Data-Driven Learning of Geometric Scattering Modules for GNNs. 1-6 - Sharu Theresa Jose, Osvaldo Simeone:
A Unified PAC-Bayesian Framework for Machine Unlearning via Information Risk Minimization. 1-6 - Yanhua Chen, Mingtao Pei, Zhengang Nie:
Recognizing Activities from Egocentric Images with Appearance and Motion Features. 1-6 - Yi Yan, Radwa Adel, Ercan E. Kuruoglu:
Adaptive Normalized LMP Estimation for Graph Signal Processing. 1-6 - Fuxiang Wang, Qing Mei, Xuhui Liu, Yao Xiao:
Optimized Spatial Matching for Visual Object Tracking. 1-6 - Jaesung Tae, Hyeongju Kim, Younggun Lee:
MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis. 1-6 - Camilo Aguilar, Mathias Ortner, Josiane Zerubia:
Small Moving Target MOT Tracking with GM-PHD Filter and Attention-Based CNN. 1-6 - Conrad D. Hougen, Lance M. Kaplan, Federico Cerutti, Alfred O. Hero III:
Uncertain Bayesian Networks: Learning from Incomplete Data. 1-6 - Bowen Deng, Aimin Jiang:
Dynamic Graph Convolutional Network: A Topology Optimization Perspective. 1-6 - Lachlan Birnie, Prasanga N. Samarasinghe, Thushara D. Abhayapala, Daniel Grixti-Cheng:
Noise RETF Estimation and Removal for Low SNR Speech Enhancement. 1-6 - Manik Kuchroo, Abhinav Godavarthi, Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Multimodal Data Visualization and Denoising with Integrated Diffusion. 1-6 - Ashkan Esmaeili, Mohsen Joneidi, Mehrdad Salimitari, Umar Khalid, Nazanin Rahnavard:
Two-Way Spectrum Pursuit for CUR Decomposition and its Application in Joint Column/Row Subset Selection. 1-6 - Théo Jourdan, Antoine Boutet, Carole Frindel:
Privacy Assessment of Federated Learning Using Private Personalized Layers. 1-6 - Yunchuan Zhang, Sharu Theresa Jose, Osvaldo Simeone:
Transfer Bayesian Meta-Learning Via Weighted Free Energy Minimization. 1-6 - Eric Guizzo, Riccardo F. Gramaccioni, Saeid Jamili, Christian Marinoni, Edoardo Massaro, Claudia Medaglia, Giuseppe Nachira, Leonardo Nucciarelli, Ludovica Paglialunga, Marco Pennese, Sveva Pepe, Enrico Rocchi, Aurelio Uncini, Danilo Comminiello:
L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing. 1-6 - Mu Xiyu, Xu Qi, Zhang Qiang, Ren Junch, Wang Hongbin, Zhou Linyi:
An Improved Diracnet Convolutional Neural Network for Haze Visibility Detection. 1-5 - Xin Lou, Han Wang:
Object Detection in SAR Via Generative Knowledge Transfer. 1-6 - Mohammad Rasool Izadi, Robert Stevenson, Laura N. Kloepper:
Affinity Mixup for Weakly Supervised Sound Event Detection. 1-6 - Ruairí de Fréin, Obinna Izima, Ali Malik:
Detecting Network State in the Presence of Varying Levels of Congestion. 1-6 - Minxu Peng, Mertcan Cokbas, Unay Dorken Gallastegi, Prakash Ishwar, Janusz Konrad, Brian Kulis, Vivek K. Goyal:
Convolutional Neural Network Denoising of Focused Ion Beam Micrographs. 1-6 - Dino Pjanic, Alexandros Sopasakis, Harsh Tataria, Fredrik Tufvesson, Andres Reial:
Learning-Based UE Classification in Millimeter-Wave Cellular Systems with Mobility. 1-6 - Gülce Turhan, Elif Vural:
Estimating Partially Observed Graph Signals by Learning Spectrally Concentrated Graph Kernels. 1-6 - Zejiang Hou, Sun-Yuan Kung:
Few-Shot Learning Via Dependency Maximization and Instance Discriminant Analysis. 1-6 - Anand Dubey, Avik Santra, Jonas Fuchs, Maximilian Lübke, Robert Weigel, Fabian Lurz:
Bayesradar : Bayesian Metric-Kalman Filter Learning for Improved and Reliable Radar Target Classification. 1-6 - Simo Särkkä, Christos Merkatas, Toni Karvonen:
Gaussian Approximations of SDES in Metropolis-Adjusted Langevin Algorithms. 1-6 - Friedrich Dörmann, Osvald Frisk, Lars Nørvang Andersen, Christian Fischer Pedersen:
Not All Noise is Accounted Equally: How Differentially Private Learning Benefits from Large Sampling Rates. 1-6 - Boyu Zhang, Aleksandar Vakanski, Min Xian:
Bi-Rads-Net: An Explainable Multitask Learning Approach for Cancer Diagnosis in Breast Ultrasound Images. 1-6 - Ming-Hsun Yang, Y.-W. Peter Hong, Jwo-Yuh Wu:
Ambiguity-Free and Efficient Sparse Phase Retrieval from Affine Measurements Under Outlier Corruption. 1-6 - Debaleena Roy, Tanaya Guha, Victor Sanchez:
Graph-Based Transform Based on Neural Networks for Intra-Prediction of Imaging Data. 1-6 - Yuying Xie, Thomas Arildsen, Zheng-Hua Tan:
Disentangled Speech Representation Learning Based on Factorized Hierarchical Variational Autoencoder with Self-Supervised Objective. 1-6 - Hassaan Hashmi, Dionysios S. Kalogerias:
Model-Free Learning of Optimal Deterministic Resource Allocations in Wireless Systems via Action-Space Exploration. 1-6 - Albert Podusenko, Bart van Erp, Dmitry Bagaev, Ismail Senöz, Bert de Vries:
Message Passing-Based Inference in the Gamma Mixture Model. 1-6 - Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia:
Adversarial Perturbation Attacks on Nested Dichotomies Classification Systems. 1-6 - Wataru Yata, Masao Yamagishi, Isao Yamada:
A Constrained Linearly Involved Generalized Moreau Enhanced Model and Its Proximal Splitting Algorithm. 1-6 - Soufiyan Bahadi, Jean Rouat, Eric Plourde:
Adaptive Approach for Sparse Representations Using the Locally Competitive Algorithm for Audio. 1-6 - Caio Davi, Ulisses M. Braga-Neto:
A Semi-Supervised Generative Adversarial Network for Prediction of Genetic Disease Outcomes. 1-6 - Swaroop Damodaran, Ram Padmanabhan, R. Maahin, Sanjeev Gurugopinath:
A Copula-Driven Unsupervised Learning Framework for Anomaly Detection with Multivariate Heterogeneous Data. 1-6 - Zhaoyan Lyu, Gholamali Aminian, Miguel R. D. Rodrigues:
Toward Minimal-Sufficiency in Regression Tasks: An Approach Based on a Variational Estimation Bottleneck. 1-6 - Dariush Salami, Stephan Sigg:
Zero-Shot Motion Pattern Recognition from 4D Point-Clouds. 1-6 - Yicong He, Andre Beckus, George K. Atia:
Scalable Community Detection in the Degree-Corrected Stochastic Block Model. 1-6 - Akram S. Awad, Ismail R. Alkhouri, George K. Atia:
Adversarial Attacks on Multi-Level Fault Detection and Diagnosis Systems. 1-6 - Guanqun Ding, Nevrez Imamoglu, Ali Caglayan, Masahiro Murakawa, Ryosuke Nakamura:
FBR-CNN: A Feedback Recurrent Network for Video Saliency Detection. 1-6 - Ken O'Hanlon, Emmanouil Benetos, Simon Dixon:
Detecting Cover Songs with Pitch Class Key-Invariant Networks. 1-6 - Hugo Gangloff, Katherine Morales, Yohan Petetin:
A General Parametrization Framework for Pairwise Markov Models: An Application to Unsupervised Image Segmentation. 1-6 - Viet-Nhat Nguyen, Mostafa Sadeghi, Elisa Ricci, Xavier Alameda-Pineda:
Deep Variational Generative Models for Audio-Visual Speech Separation. 1-6 - You-De Huang, Y.-W. Peter Hong:
Distributed Dictionary Learning Over Heterogeneous Clients Using Local Adaptive Dictionaries. 1-6 - Ruixian Fan, Mingtao Pei:
Lightweight Forest Fire Detection Based on Deep Learning. 1-6 - Y.-W. Peter Hong, Wen-Yang Chen, Hao-Tang Chang:
Specrank: Ranking by Pairwise Comparisons from Specialty Workers in a Crowdsourced Setting. 1-6 - Ian Pradhan, Siwei Lyu:
Understanding Linear Style Transfer Auto-Encoders. 1-5 - Aaron Valero Puche, Sukhan Lee:
Caesynth: Real-Time Timbre Interpolation and Pitch Control with Conditional Autoencoders. 1-6 - Xinlei Ren, Lianwu Chen, Xiguang Zheng, Chenglin Xu, Xu Zhang, Chen Zhang, Liang Guo, Bing Yu:
A Neural Beamforming Network for B-Format 3D Speech Enhancement and Recognition. 1-6 - Shogo Seki, Haruka Taga, Tomoki Toda:
Singing Fundamental Frequency Contour Generation Using Generalized Command-Response Model and Score-Conditional Variational Autoencoder. 1-3 - Zidi Gao, Yiwen He, Ercan Engin Kuruoglu:
A Hybrid Model Integrating LSTM and Garch for Bitcoin Price Prediction. 1-6 - Xubo Liu, Turab Iqbal, Jinzheng Zhao, Qiushi Huang, Mark D. Plumbley, Wenwu Wang:
Conditional Sound Generation Using Neural Discrete Time-Frequency Representation Learning. 1-6 - Yong Cai, Mengwei Chen, Yifei Feng, Zheng Ming:
A Placement Angle Detection Method of Recyclable Object for Garbage Power Generation. 1-5 - Jaspreet Singh, Chandan Singh:
Bag of Groups of Convolutional Features Model for Visual Object Recognition. 1-6 - Aswathy Madhu, Suresh Kumaraswamy:
SiamNet: Siamese CNN Based Similarity Model for Adversarially Generated Environmental Sounds. 1-6 - Pierre Rougé, Ali Moukadem, Alain Dieterlen, Antoine Boutet, Carole Frindel:
Anonymizing Motion Sensor Data Through Time-Frequency Domain. 1-6 - Xiaochuan Ma, Lifeng Lai, Shuguang Cui:
Bayesian Two-Stage Sequential Change Diagnosis Via Multi-Sensor Array. 1-6 - Xiaoxue Zhao, Cuiwei Liu, Xiangbin Shi:
Early Fusion Graph Convolutional Network for Skeleton-Based Action Recognition. 1-6 - Alireza Nooraiepour, Waheed U. Bajwa, Narayan B. Mandayam:
Hyphylearn: A Domain Adaptation-Inspired Approach to Classification Using Limited Number of Training Samples. 1-6 - Mehrdad Pournaderi, Yu Xiang:
Differentially Private Variable Selection via the Knockoff Filter. 1-6 - Wenming Tang, Lebin Zhou, Yuanhao Gong:
Real-Time Optimizing Weighted Gaussian Curvature for 4K Videos. 1-6 - Emmanouil Gionanidis, Constantine Kotropoulos, Myrsini Ntemi:
Opinion Recommendation Using Coverage for Adaptive Prediction. 1-6 - Shuai Xu, Dongliang Chang, Jiyang Xie, Zhanyu Ma:
GRAD-CAM Guided Channel-Spatial Attention Module for Fine-Grained Visual Classification. 1-6 - Xiaochuan Ma, Lifeng Lai, Shuguang Cui:
A Deep Q-Network Based Approach for Online Bayesian Change Point Detection. 1-6 - Eero Siivola, Akash Kumar Dhaka, Michael Riis Andersen, Javier González, Pablo Garcia Moreno, Aki Vehtari:
Preferential Batch Bayesian Optimization. 1-6 - Aleksandar Vakanski, Min Xian:
Evaluation of Complexity Measures for Deep Learning Generalization in Medical Image Analysis. 1-6 - Jhon Lopez, Carlos Hinojosa, Henry Arguello:
Fast Subspace Clustering Algorithm with Efficient Similarity-Constrained Sampling for Hyperspectral Images. 1-6 - Rohan T. Money, Joshin Krishnan, Baltasar Beferull-Lozano:
Random Feature Approximation for Online Nonlinear Graph Topology Identification. 1-6 - Jinyan Liu, Longbin Yan, Jie Chen:
A Coarse-to-Fine Object Detection Framework for High-Resolution Images with Sparse Objects. 1-6 - Michela Carlotta Massi, Francesca Ieva:
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification. 1-6 - Yifan Tai, Zhenyu Sun, Zixuan Yao:
Content-Based Recommendation Using Machine Learning. 1-4 - Victor Sanchez, Miguel Hernández-Cabronero, Joan Serra-Sagristà:
Block-Wise Intra-Prediction of Imaging Data Based on Overfitted Neural Networks with On-Line Learning. 1-6 - Brayan Monroy, Jorge Bacca, Henry Arguello:
Deep Low-Dimensional Spectral Image Representation for Compressive Spectral Reconstruction. 1-6 - Jose Agustin Barrachina, Chenfang Ren, Gilles Vieillard, Christèle Morisseau, Jean Philippe Ovarlez:
About the Equivalence Between Complex-Valued and Real-Valued Fully Connected Neural Networks - Application to Polinsar Images. 1-6 - Xinjie Lan, Bin Zhu, Charles Boncelet, Kenneth E. Barner:
Beyond the Bias Variance Trade-Off: A Mutual Information Trade-Off in Deep Learning. 1-6 - Zahir Alsulaimawi, Huaping Liu:
Distributed Variational Information Bottleneck for IOT Environments. 1-6 - Yunfu Song, Huahuan Zheng, Zhijian Ou:
An Empirical Comparison of Joint-Training and Pre-Training for Domain-Agnostic Semi-Supervised Learning Via Energy-Based Models. 1-6 - Eylem Tugçe Güneyi, Abdullah Canbolat, Elif Vural:
Learning Parametric Time-Vertex Graph Processes from Incomplete Realizations. 1-6 - Vasileios Mygdalis, Anastasios Tefas, Ioannis Pitas:
Introducing K-Anonymity Principles to Adversarial Attacks for Privacy Protection in Image Classification Problems. 1-6 - Mahiout Thomas, Fillatre Lionel, Deruaz-Pepin Laurent:
Explainable Deep Learning Detection of Gaussian Propeller Noise with Unknown Signal-to-Noise Ratio. 1-6 - Isaac Sebenius, Alexander Campbell, Sarah E. Morgan, Edward T. Bullmore, Pietro Liò:
Multimodal Graph Coarsening for Interpretable, MRI-Based Brain Graph Neural Network. 1-6
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last updated on 2024-12-08 01:33 CET by the dblp team
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