An overview of deep semi-supervised learning
Deep neural networks demonstrated their ability to provide remarkable performances on a
wide range of supervised learning tasks (eg, image classification) when trained on extensive …
wide range of supervised learning tasks (eg, image classification) when trained on extensive …
New avenues in opinion mining and sentiment analysis
New Avenues in Opinion Mining and Sentiment Analysis Page 1 New Avenues in Opinion
Mining and Sentiment Analysis Erik Cambria, Member, IEEE, Björn Schuller, Member, IEEE …
Mining and Sentiment Analysis Erik Cambria, Member, IEEE, Björn Schuller, Member, IEEE …
Self-training with noisy student improves imagenet classification
We present a simple self-training method that achieves 88.4% top-1 accuracy on ImageNet,
which is 2.0% better than the state-of-the-art model that requires 3.5 B weakly labeled …
which is 2.0% better than the state-of-the-art model that requires 3.5 B weakly labeled …
W2v-bert: Combining contrastive learning and masked language modeling for self-supervised speech pre-training
Motivated by the success of masked language modeling (MLM) in pre-training natural
language processing models, we propose w2v-BERT that explores MLM for self-supervised …
language processing models, we propose w2v-BERT that explores MLM for self-supervised …
[BOOK][B] Sentiment analysis and opinion mining
B Liu - 2022 - books.google.com
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions,
sentiments, evaluations, attitudes, and emotions from written language. It is one of the most …
sentiments, evaluations, attitudes, and emotions from written language. It is one of the most …
Twitter mood predicts the stock market
Behavioral economics tells us that emotions can profoundly affect individual behavior and
decision-making. Does this also apply to societies at large, ie can societies experience …
decision-making. Does this also apply to societies at large, ie can societies experience …
A survey on opinion mining and sentiment analysis: tasks, approaches and applications
With the advent of Web 2.0, people became more eager to express and share their opinions
on web regarding day-to-day activities and global issues as well. Evolution of social media …
on web regarding day-to-day activities and global issues as well. Evolution of social media …
Lexicon-based methods for sentiment analysis
We present a lexicon-based approach to extracting sentiment from text. The Semantic
Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic …
Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic …
Pushing the limits of semi-supervised learning for automatic speech recognition
We employ a combination of recent developments in semi-supervised learning for automatic
speech recognition to obtain state-of-the-art results on LibriSpeech utilizing the unlabeled …
speech recognition to obtain state-of-the-art results on LibriSpeech utilizing the unlabeled …
Opinion mining and sentiment analysis
An important part of our information-gathering behavior has always been to find out what
other people think. With the growing availability and popularity of opinion-rich resources …
other people think. With the growing availability and popularity of opinion-rich resources …