Multi Task Learning

October 10, 2022

Visually Similar Products Retrieval for Shopsy
Prajit Nadkarni, Narendra Varma Dasararaju
Multi Task Learning Visual Search Product Retrieval Multi Attribute

October 8, 2022

Multi-Task Dynamical Systems
Alex Bird, Christopher K. I. Williams, Christopher Hawthorne
Multi Task Learning Multi Task Dynamical System Time Series Model
Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task
Cong Ma, Yaping Zhang, Mei Tu, Xu Han, Linghui Wu, Yang Zhao, Yu Zhou
Multi Task Learning Image Translation Human Translation Multi Task Training Image Machine Translation
Data-Efficiency with a Single GPU: An Exploration of Transfer Methods for Small Language Models
Alon Albalak, Akshat Shrivastava, Chinnadhurai Sankar, Adithya Sagar, Mike Ross
Large Language Model Language Model Multi Task Learning Instruction Tuning Environment Exploration Formality Transfer Single GPU Smaller Language Model Data Efficiency

October 6, 2022

Causal Inference for Chatting Handoff
Shanshan Zhong, Jinghui Qin, Zhongzhan Huang, Daifeng Li
Multi Task Learning Causal Inference Causal Graph Robot Handover Event Causality Identification

October 3, 2022

CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning
Carmelo Scribano, Giorgia Franchini, Ignacio Sañudo Olmedo, Marko Bertogna
Multi Task Learning Multitask Learning Vehicle Interaction Vehicle Perception Perception Task

September 30, 2022

Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
Ye Tian, Haolei Weng, Yang Feng
Transfer Learning Multi Task Learning Multi Task Unsupervised Learning Gaussian Mixture Model Single Task Learning Mixture Training

September 27, 2022

Design Perspectives of Multitask Deep Learning Models and Applications
Yeshwant Singh, Anupam Biswas, Angshuman Bora, Debashish Malakar, Subham Chakraborty, Suman Bera
Financial Application Multi Task Learning Task Relationship Learning Task Multi Tasking Model

September 26, 2022

TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding
Surya Kant Sahu
Data Augmentation Multi Task Learning Meta Learning Human Machine Automatic Speech Recognition Hypothesis Task Diversity

September 24, 2022

Highly Scalable Task Grouping for Deep Multi-Task Learning in Prediction of Epigenetic Events
Mohammad Shiri, Jiangwen Sun
Deep Neural Network Human Prediction Multi Task Learning Multi Task Single Task Learning Genome Wide Association Study DNA Methylation Epigenetic State Input

September 23, 2022

Grouped Adaptive Loss Weighting for Person Search
Yanling Tian, Di Chen, Yunan Liu, Shanshan Zhang, Jian Yang
Multi Task Learning Person Re Identification Adaptive Loss Person Search

September 21, 2022

September 20, 2022

Collaborative Anomaly Detection
Ke Bai, Aonan Zhang, Zhizhong Li, Ricardo Heano, Chong Wang, Lawrence Carin
Anomaly Detection Multi Task Learning Single Task Learning Task Embeddings Collaborative Anomaly Detection

September 14, 2022

Integrating Form and Meaning: A Multi-Task Learning Model for Acoustic Word Embeddings
Badr M. Abdullah, Bernd Möbius, Dietrich Klakow
Multi Task Learning Multiple Meaning First Integral Acoustic Word Embeddings Lexical Knowledge Lexical Representation Lexical Processing

September 13, 2022

MLT-LE: predicting drug-target binding affinity with multi-task residual neural networks
Elizaveta Vinogradova, Karina Pats, Ferdinand Molnár, Siamac Fazli
Multi Task Learning Multi Task Drug Discovery Estimated Team Strength Residual Neural Network Drug Target

September 9, 2022

Joint Alignment of Multi-Task Feature and Label Spaces for Emotion Cause Pair Extraction
Shunjie Chen, Xiaochuan Shi, Jingye Li, Shengqiong Wu, Hao Fei, Fei Li, Donghong Ji
Multi Task Learning Multi Task Label Space Emotion Embeddings Emotion Cause Pair Extraction Task Alignment Joint Alignment

September 6, 2022

Sequential Cross Attention Based Multi-task Learning
Sunkyung Kim, Hyesong Choi, Dongbo Min
Multi Task Learning Multi Scale Attention Module Self Attention Module Cross Task Attention Sequential Multi Task Learning

September 4, 2022

Joint Prediction of Meningioma Grade and Brain Invasion via Task-Aware Contrastive Learning
Tianling Liu, Wennan Liu, Lequan Yu, Liang Wan, Tong Han, Lei Zhu
Multi Task Learning Joint predictioN Task Specific Feature Task Contrastive Learning

September 2, 2022

A Method for Discovering Novel Classes in Tabular Data
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
Multi Task Learning Practical Method Tabular Data Novel Class Discovery Classification Datasets Heterogeneous Tabular Data

Papers

Visually Similar Products Retrieval for Shopsy

Multi-Task Dynamical Systems

Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task

Data-Efficiency with a Single GPU: An Exploration of Transfer Methods for Small Language Models

Causal Inference for Chatting Handoff

CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning

Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models

Design Perspectives of Multitask Deep Learning Models and Applications

TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding

Highly Scalable Task Grouping for Deep Multi-Task Learning in Prediction of Epigenetic Events

Grouped Adaptive Loss Weighting for Person Search

Grape Cold Hardiness Prediction via Multi-Task Learning

Extreme Multi-Domain, Multi-Task Learning With Unified Text-to-Text Transfer Transformers

Collaborative Anomaly Detection

Integrating Form and Meaning: A Multi-Task Learning Model for Acoustic Word Embeddings

MLT-LE: predicting drug-target binding affinity with multi-task residual neural networks

Joint Alignment of Multi-Task Feature and Label Spaces for Emotion Cause Pair Extraction

Sequential Cross Attention Based Multi-task Learning

Joint Prediction of Meningioma Grade and Brain Invasion via Task-Aware Contrastive Learning

A Method for Discovering Novel Classes in Tabular Data