Контакты/Проезд  Доставка и Оплата Помощь/Возврат
История
  +7(495) 980-12-10
  пн-пт: 10-18 сб,вс: 11-18
  shop@logobook.ru
   
    Поиск книг                    Поиск по списку ISBN Расширенный поиск    
Найти
  Зарубежные издательства Российские издательства  
Авторы | Каталог книг | Издательства | Новинки | Учебная литература | Акции | Хиты | |
 

Artificial Neural Networks and Machine Learning - ICANN 2021: 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, Septe, Farkas Igor, Masulli Paolo, Otte Sebastian


Варианты приобретения
Цена: 13974.00р.
Кол-во:
Наличие: Поставка под заказ.  Есть в наличии на складе поставщика.
Склад Америка: Есть  
При оформлении заказа до: 2025-08-18
Ориентировочная дата поставки: конец Сентября - начало Октября
При условии наличия книги у поставщика.

Добавить в корзину
в Мои желания

Автор: Farkas Igor, Masulli Paolo, Otte Sebastian
Название:  Artificial Neural Networks and Machine Learning - ICANN 2021: 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, Septe
ISBN: 9783030863821
Издательство: Springer
Классификация:






ISBN-10: 3030863824
Обложка/Формат: Paperback
Страницы: 720
Вес: 0.99 кг.
Дата издания: 11.09.2021
Язык: English
Размер: 23.39 x 15.60 x 3.66 cm
Ссылка на Издательство: Link
Поставляется из: Германии
Описание:

Representation learning.- SageDy: A Novel Sampling and Aggregating based Representation Learning Approach for Dynamic Networks.- CuRL: Coupled Representation Learning of cards and merchants to detect transaction frauds.- Revisiting Loss Functions for Person Re-Identification.- Statistical Characteristics of Deep Representations: An Empirical Investigation.- Reservoir computing.- Unsupervised Pretraining of Echo State Networks for Onset Detection.- Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs.- Which Hype for my New Task? Hints and Random Search for Echo State Networks Hyperparameters.- Semi- and Unsupervised learning.- A new Nearest Neighbor Median Shift Clustering for Binary Data.- Self-supervised Multi-view Clustering for Unsupervised Image Segmentation.- Evaluate Pseudo Labeling and CNN for multi-variate time series classification in low-data regimes.- Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP).- Short Text Clustering with A Deep Multi-Embedded Self-Supervised Model.- Brain-like approaches to unsupervised learning of hidden representations - a comparative study.- Spiking neural networks.- A Subthreshold Spiking Neuron Circuit Based on the Izhikevich Model.- SiamSNN: Siamese Spiking Neural Networks for Energy-Efficient Object Tracking.- The principle of weight divergence facilitation for unsupervised pattern recognition in spiking neural networks.- Algorithm For 3D-Chemotaxis Using Spiking Neural Network.- Signal Denoising with Recurrent Spiking Neural Networks and Active Tuning.- Dynamic Action Inference with Recurrent Spiking Neural Networks.- End-to-end Spiking Neural Network for Speech Recognition Using Resonating Input Neurons.- Text understanding I.- Visual-Textual Semantic Alignment Network for Visual Question Answering.- Which and Where to Focus: A Simple yet Accurate Framework for Arbitrary-Shaped Nearby Text Detection in Scene Images.- STCP: An Efficient Model Combing Subject Triples and Constituency Parsing for Recognizing Textual Entailment.- A Latent Variable Model with Hierarchical structure and GPT-2 for long text generation.- A Scoring Model Assisted by Frequency for Multi-Document Summarization.- A Strategy for Referential Problem in Low-Resource Neural Machine Translation.- A Unified Summarization Model with Semantic Guide and Keyword Coverage Mechanism.- Hierarchical Lexicon Embedding Architecture for Chinese Named Entity Recognition.- Evidence Augment for Multiple-Choice Machine Reading Comprehension by Weak Supervision.- Resolving Ambiguity in Hedge Detection by Automatic Generation of Linguistic Rules.- Text understanding II.- Detecting Scarce Emotions Using BERT and Hyperparameter Optimization.- Design and Evaluation of Deep Learning Models for Real-Time Credibility Assessment in Twitter.- T-Bert: A Spam Review Detection Model Combining Group Intelligence and Personalized Sentiment Information.- Graph Enhanced BERT for Stance-aware Rumor Verification on Social Media.- Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction.- Learning to Remove: Towards Isotropic Pre-trained BERT Embedding.- ExBERT: An External Knowledge Enhanced BERT for Natural Language Inference.- Multi-Features-Based Automatic Clinical Coding for Chinese ICD-9-CM-3.- Style as Sentiment versus Style as Formality: the same or different?.- Transfer and meta learning.- Low-resource Neural Machine Translation Using XLNet Pre-training Model.- Self-Learning for Received Signal Strength MapReconstruction with Neural Architecture Search.- Propagation-aware Social Recommendation by Transfer Learning.- Evaluation of Transfer Learning for Visual Road Condition Assessment.- EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture Search.- DVAMN: Dual Visual Attention Matching Network for Zero-Shot Action Recognition.- Dynami



ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
   В Контакте     В Контакте Мед  Мобильная версия