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Multi-Task Learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

( Image credit: Cross-stitch Networks for Multi-task Learning )

Papers

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Showing 3601–3650 of 3687 papers

TitleStatusHype
Learning Representations for Text-level Discourse Parsing—0
Matrix and Tensor Factorization Methods for Natural Language Processing—0
Baidu Translate: Research and Products—0
Question Answering over Freebase with Multi-Column Convolutional Neural Networks—0
A Refined End-to-End Discourse Parser—0
Framework for Multi-task Multiple Kernel Learning and Applications in Genome Analysis—0
Learning Multiple Tasks with Multilinear Relationship Networks—0
Multi-Feature Max-Margin Hierarchical Bayesian Model for Action Recognition—0
Lifelong Machine Learning for Topic Modeling and Beyond—0
Multi-Task Deep Visual-Semantic Embedding for Video Thumbnail Selection—0
ECNU: Using Traditional Similarity Measurements and Word Embedding for Semantic Textual Similarity Estimation—0
Classifying Tweet Level Judgements of Rumours in Social Media—0
Hyper-Class Augmented and Regularized Deep Learning for Fine-Grained Image Classification—0
Automatically Scoring Freshman Writing: A Preliminary Investigation—0
Deeply Learned Attributes for Crowded Scene Understanding—0
Deep sparse multi-task learning for feature selection in Alzheimer’s disease diagnosis—0
Multi-task additive models with shared transfer functions based on dictionary learning—0
Multi-Task Word Alignment Triangulation for Low-Resource Languages—0
Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval—0
Learning Multiple Visual Tasks while Discovering their Structure—0
Convex Learning of Multiple Tasks and their StructureCode0
Automatic Noun Compound Interpretation using Deep Neural Networks and Word Embeddings—0
A Unified Perspective on Multi-Domain and Multi-Task Learning—0
Deep Structured Output Learning for Unconstrained Text Recognition—0
Curriculum Learning of Multiple Tasks—0
QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models—0
Multi-Task Metric Learning on Network Data—0
Joint Emotion Analysis via Multi-task Gaussian Processes—0
Multi-task Sparse Structure Learning—0
Task-group Relatedness and Generalization Bounds for Regularized Multi-task Learning—0
Conic Multi-Task ClassificationCode0
Convergence rate of Bayesian tensor estimator: Optimal rate without restricted strong convexity—0
UoW: Multi-task Learning Gaussian Process for Semantic Textual Similarity—0
Self-Learning Camera: Autonomous Adaptation of Object Detectors to Unlabeled Video Streams—0
Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network—0
Two-Stream Convolutional Networks for Action Recognition in VideosCode0
Transductive Learning for Multi-Task Copula Processes—0
Predicting Multiple Attributes via Relative Multi-task Learning—0
Decorrelating Semantic Visual Attributes by Resisting the Urge to Share—0
A Recursive Recurrent Neural Network for Statistical Machine Translation—0
SHEF-Lite 2.0: Sparse Multi-task Gaussian Processes for Translation Quality Estimation—0
Surpassing Human-Level Face Verification Performance on LFW with GaussianFace—0
Pareto-Path Multi-Task Multiple Kernel Learning—0
Multi-task Feature Selection based Anomaly Detection—0
Mixed-norm Regularization for Brain Decoding—0
A Unifying Framework for Typical Multi-Task Multiple Kernel Learning Problems—0
A Fused Elastic Net Logistic Regression Model for Multi-Task Binary Classification—0
Multi-Task Classification Hypothesis Space with Improved Generalization Bounds—0
Non-Linear Domain Adaptation with Boosting—0
Learning Feature Selection Dependencies in Multi-task Learning—0
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All datasetsQM9Cityscapes testNYUv2OMNIGLOTCelebAUTKFacewireframe dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PCGrad∆m%125.7—Unverified
2CAGrad∆m%112.8—Unverified
3IMTL-G∆m%77.2—Unverified
4Nash-MTL∆m%62—Unverified
5BayesAgg-MTL∆m%53.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinMTLmIoU76.41—Unverified
2Nash-MTLmIoU75.41—Unverified
3MultiObjectiveOptimizationmIoU66.63—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinMTLMean IoU58.14—Unverified
2Nash-MTLMean IoU40.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Gumbel-Matrix RoutingAverage Accuracy93.52—Unverified
2Mixture-of-ExpertsAverage Accuracy92.19—Unverified
#ModelMetricClaimedVerifiedStatus
1MGDA-UBError8.25—Unverified
#ModelMetricClaimedVerifiedStatus
1BayesAgg-MTLdelta_m-2.23—Unverified
#ModelMetricClaimedVerifiedStatus
1LETRFH83.3—Unverified