Search Results for author:
Found 21 papers, 15 papers with code
Supervision Interpolation via LossMix: Generalizing Mixup for Object Detection and Beyond
The success of data mixing augmentations in image classification tasks has been well-received.
Toward Edge-Efficient Dense Predictions with Synergistic Multi-Task Neural Architecture Search
Our first key insight is that MultiTask Learning (MTL) and hardware-aware Neural Architecture Search (NAS) can work in synergy to greatly benefit on-device Dense Predictions (DP).
Ranked #105 on
Semantic Segmentation
on NYU Depth v2
Hardware Aware Neural Architecture Search
Neural Architecture Search
+2
Automatic Post-Editing for Vietnamese
Automatic post-editing (APE) is an important remedy for reducing errors of raw translated texts that are produced by machine translation (MT) systems or software-aided translation.
Any-Width Networks
To address these constraints, we propose the Any-Width Network (AWN), an adjustable-width CNN architecture and associated training routine that allow for fine-grained control over speed and accuracy during inference.
WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets
In this paper, we provide an overview of the WNUT-2020 shared task on the identification of informative COVID-19 English Tweets.
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings
We propose a simple yet effective embedding model to learn quaternion embeddings for entities and relations in knowledge graphs.
A Label Attention Model for ICD Coding from Clinical Text
In this paper, we propose a new label attention model for automatic ICD coding, which can handle both the various lengths and the interdependence of the ICD code related text fragments.
Ranked #6 on
Medical Code Prediction
on MIMIC-III
HSD Shared Task in VLSP Campaign 2019:Hate Speech Detection for Social Good
The paper describes the organisation of the "HateSpeech Detection" (HSD) task at the VLSP workshop 2019 on detecting the fine-grained presence of hate speech in Vietnamese textual items (i. e., messages) extracted from Facebook, which is the most popular social network site (SNS) in Vietnam.
BERTweet: A pre-trained language model for English Tweets
We present BERTweet, the first public large-scale pre-trained language model for English Tweets.
Ranked #1 on
Sentiment Analysis
on TweetEval
Mapped Convolutions
We present a versatile formulation of the convolution operation that we term a "mapped convolution."
Identifying Patients with Pain in Emergency Departments using Conventional Machine Learning and Deep Learning
Pain is the main symptom that patients present with to the emergency department (ED).
ETNLP: a visual-aided systematic approach to select pre-trained embeddings for a downstream task
We demonstrate the effectiveness of the proposed approach on our pre-trained word embedding models in Vietnamese to select which models are suitable for a named entity recognition (NER) task.
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization
In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples (subject, relation, object).
Ranked #40 on
Link Prediction
on WN18RR
Finding your Lookalike: Measuring Face Similarity Rather than Face Identity
In this work we propose the new, subjective task of quantifying perceived face similarity between a pair of faces.
A Capsule Network-based Embedding Model for Search Personalization
After that, the 3-column matrix is fed into a deep learning architecture to re-rank the search results returned by a basis ranker.
NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter
This paper describes our NIHRIO system for SemEval-2018 Task 3 "Irony detection in English tweets".
VnCoreNLP: A Vietnamese Natural Language Processing Toolkit
We present an easy-to-use and fast toolkit, namely VnCoreNLP---a Java NLP annotation pipeline for Vietnamese.
From Word Segmentation to POS Tagging for Vietnamese
This paper presents an empirical comparison of two strategies for Vietnamese Part-of-Speech (POS) tagging from unsegmented text: (i) a pipeline strategy where we consider the output of a word segmenter as the input of a POS tagger, and (ii) a joint strategy where we predict a combined segmentation and POS tag for each syllable.
A Fast and Accurate Vietnamese Word Segmenter
We propose a novel approach to Vietnamese word segmentation.
Search Personalization with Embeddings
Recent research has shown that the performance of search personalization depends on the richness of user profiles which normally represent the user's topical interests.
