Artificial Neural Networks and Machine Learning - ICANN 2021 : 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part IV / edited by Igor Farkaš, Paolo Masulli, Sebastian Otte, Stefan Wermter.

Format:

Book

Contributor:

Farkaš, Igor., Editor.

Masulli, Paolo, Editor.

Otte, Sebastian., Editor.

Wermter, Stefan, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Theoretical computer science and general issues 2512-2029 ; SL 1, 12894

Theoretical Computer Science and General Issues, 2512-2029 ; 12894

Language:

English

Subjects (All):

Artificial intelligence.

Social sciences-Data processing.

Education-Data processing.

Application software.

Computer engineering.

Computer networks.

Image processing-Digital techniques.

Computer vision.

Artificial Intelligence.

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Computer and Information Systems Applications.

Computer Engineering and Networks.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Local Subjects:

Artificial Intelligence.

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Computer and Information Systems Applications.

Computer Engineering and Networks.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Physical Description:

1 online resource (XXIV, 703 pages) : 242 illustrations, 210 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as model compression, multi-task and multi-label learning, neural network theory, normalization and regularization methods, person re-identification, recurrent neural networks, and reinforcement learning. *The conference was held online 2021 due to the COVID-19 pandemic.

Contents:

Model compression

Blending Pruning Criteria for Convolutional Neural Networks

BFRIFP: Brain Functional Reorganization Inspired Filter Pruning

CupNet - Pruning a network for geometric data

Pruned-YOLO: Learning Efficient Object Detector Using Model Pruning

Gator: Customizable Channel Pruning of Neural Networks with Gating

Multi-task and multi-label learning

MMF: Multi-Task Multi-Structure Fusion for Hierarchical Image Classification

GLUNet: Global-Local Fusion U-Net for 2D Medical Image Segmentation

Textbook Question Answering with Multi-type Question Learning and Contextualized Diagram Representation

A Multi-Task MRC Framework for Chinese Emotion Cause and Experiencer Extraction

Fairer Machine Learning Through Multi-objective Evolutionary Learning

Neural network theory

Single neurons with delay-based learning can generalise between time-warped patterns

Estimating Expected Calibration Errors

LipBAB: Computing exact Lipschitz constant of ReLU networks

Nonlinear Lagrangean Neural Networks

Normalization and Regularization Methods

Energy Conservation in Infinitely Wide Neural-Networks

Class-Similarity Based Label Smoothing for Confidence Calibration

Jacobian Regularization for Mitigating Universal Adversarial Perturbations

Layer-wise Activation Cluster Analysis of CNNs to Detect Out-of-Distribution Samples

Weight and Gradient Centralization in Deep Neural Networks

LocalNorm: Robust Image Classification through Dynamically Regularized Normalization

Channel Capacity of Neural Networks

RIAP: A method for Effective Receptive Field Rectification

Curriculum Learning Revisited: Incremental Batch Learning with Instance Typicality Ranking

Person re-identification

Interesting Receptive Region and Feature Excitation for Partial Person Re-Identification

Improved Occluded Person Re-Identification with Multi-feature Fusion

Joint Weights-averaged and Feature-separated Learning for Person Re-identification

Semi-Hard Margin Support Vector Machines for Personal Authentication with an Aerial Signature Motion.-Recurrent neural networks

Dynamic identification of stop locations from GPS trajectories based on their temporal and spatial characteristics

Separation of Memory and Processing in Dual Recurrent Neural Networks

Predicting Landfall's Location and Time of a Tropical Cyclone Using Reanalysis Data

Latent State Inference in a Spatiotemporal Generative Model

Deep learning models and interpretations for multivariate discrete-valued event sequence prediction

End-to-End On-Line Multi-Object Tracking on Sparse Point Clouds Using Recurrent Convolutional Networks

M-ary Hopfield Neural Network based Associative Memory Formulation: Limit-cycle based Sequence Storage and Retrieval

Training Many-to-Many Recurrent Neural Networks with Target Propagation

Early Recognition of Ball Catching Success in Clinical Trials with RNN-Based Predictive Classification

Precise temporal P300 detection in Brain Computer Interface EEG signals using a Long-Short Term Memory

Noise Quality and Super-Turing Computation in Recurrent Neural Networks

Reinforcement learning I

Learning to Plan via a Multi-Step Policy Regression Method

Behaviour-conditioned policies for cooperative reinforcement learning tasks

Integrated Actor-Critic for Deep Reinforcement Learning

Learning to Assist Agents by Observing Them

Reinforcement Syntactic Dependency Tree Reasoning for Target-Oriented Opinion Word Extraction

Learning distinct strategies for heterogeneous cooperative multi-agent reinforcement learning

MAT-DQN: Toward Interpretable Multi-Agent Deep Reinforcement Learning for Coordinated Activities

Selection-Expansion: a unifying framework for motion-planning and diversity search algorithms

A Hand Gesture Recognition System using EMG and Reinforcement Learning: a Q-Learning Approach

Reinforcement learning II

Reinforcement learning for the privacy preservation and manipulation of eye tracking data

Reinforcement Symbolic Learning

Deep Reinforcement Learning for Job Scheduling on Cluster

Independent Deep Deterministic Policy Gradient Reinforcement Learning in Cooperative Multiagent Pursuit Games

Avoid Overfitting in Deep Reinforcement Learning: Increasing Robustness through Decentralized Control

Advances in Adaptive Skill Acquisition

Aspect-Based Sentiment Classification with Reinforcement Learning and Local Understanding

Latent dynamics for artefact-free character animation via data-driven reinforcement learning

Intrinsic Motivation Model Based on Reward Gating.

Other Format:

Printed edition:

ISBN:

978-3-030-86380-7

9783030863807

Access Restriction:

Restricted for use by site license.