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[PDF] Top 20 Multi Task Networks with Universe, Group, and Task Feature Learning

Has 10000 "Multi Task Networks with Universe, Group, and Task Feature Learning" found on our website. Below are the top 20 most common "Multi Task Networks with Universe, Group, and Task Feature Learning".

Multi Task Networks with Universe, Group, and Task Feature Learning

Multi Task Networks with Universe, Group, and Task Feature Learning

... that learning group features can overcome the ...real task structure. To tackle this is- sue, learning task structures with features jointly (Zhang et ...defined task groups, ... See full document

11

Efficient and Scalable Multi-Task Regression on Massive Number of Tasks

Efficient and Scalable Multi-Task Regression on Massive Number of Tasks

... Single-task learning (STL), which learns a single model by pooling together the data from all the tasks and Independent task learning (ITL), which learns each task ...between ... See full document

8

Union Support Recovery in Multi-task Learning

Union Support Recovery in Multi-task Learning

... the group Lasso performs better than the Lasso for the case where there is a lot of feature sharing between different ...the group Lasso does not have optimal dependence on k in the sparse non-zero ... See full document

21

A survey of multi-task learning methods in chemoinformatics

A survey of multi-task learning methods in chemoinformatics

... neural networks, can naturally work with missing values by ignoring the error contribution from missing values when calculating the loss for ...useful feature of Macau is the ability to work with ... See full document

11

Latent Multi-Task Architecture Learning

Latent Multi-Task Architecture Learning

... Another line of work looks into separating the learned space into a private (i.e. task-specific) and shared space (Salz- mann et al. 2010; Virtanen, Klami, and Kaski 2011) to more explicitly capture the difference ... See full document

8

Multi Task Active Learning for Neural Semantic Role Labeling on Low Resource Conversational Corpus

Multi Task Active Learning for Neural Semantic Role Labeling on Low Resource Conversational Corpus

... primary task (SRL) (Zhou and Xu, 2015) and softmax layer for the auxiliary ...auxiliary task acts as a regularization method (Caruana, ...Neural Networks as Characters Encoder (Ma and Hovy, 2016), to ... See full document

8

Minimum Description Length Penalization for Group and Multi-Task Sparse Learning

Minimum Description Length Penalization for Group and Multi-Task Sparse Learning

... Thus, knowledge can only be fruitfully transferred between the shared senses of different words, even though the models being learned are for disambiguating different senses of a single word. To address this problem, we ... See full document

40

Identifying beneficial task relations for multi task learning in deep neural networks

Identifying beneficial task relations for multi task learning in deep neural networks

... the learning curves for the main and auxiliary tasks are the best pre- dictors of MTL ...the learning curve features seem less predictive, and the gra- dients around 20-30% seem most important, af- ter the ... See full document

6

Emotion Cause Pair Extraction: A New Task to Emotion Analysis in Texts

Emotion Cause Pair Extraction: A New Task to Emotion Analysis in Texts

... the task of emo- tion cause extraction (ECE) and defined this task as extracting the word-level causes that lead to the given emotions in ...same task settings, there were some other individual ... See full document

10

Deep learning for multi task plant phenotyping

Deep learning for multi task plant phenotyping

... Our task is to locate and count wheat spikes and spikelets in the ACID dataset. Each image may contain a number of spikes, each of which will contain numerous spikelets. Both spikes and spikelets may appear very ... See full document

9

Multi-Stage Multi-Task Feature Learning

Multi-Stage Multi-Task Feature Learning

... for multi-task sparse feature learning based on a novel non-convex ...a Multi-Stage Multi-Task Feature Learning (MSMTFL) algorithm; we also provide intuitive ... See full document

32

Multi Task Learning of Keyphrase Boundary Classification

Multi Task Learning of Keyphrase Boundary Classification

... the task of detecting keyphrases in sci- entific articles and labelling them with re- spect to predefined ...this task is so far un- derexplored, partly due to the lack of la- belled ...of multi-word ... See full document

6

Concept Classification with Bayesian Multi task Learning

Concept Classification with Bayesian Multi task Learning

... of multi-task learning, results were obtained when assuming no coupling between datasets (s = 0) as well as when assuming a very strong coupling between datasets (s = ...the multi-task ... See full document

8

When does deep multi task learning work for loosely related document classification tasks?

When does deep multi task learning work for loosely related document classification tasks?

... Multi-task learning has seen a revival in recent years, amplified by the success of deep learning ...techniques. Multi-task learning algorithms have been proven to lead to ... See full document

8

The transition from concrete to formal thinking

The transition from concrete to formal thinking

... 1 Changes of measures of efficiency in learning the Pour Group Task with age 282 9.3.2 The relationship of measures of efficiency in learning the Pour Group Task to mathematical and gene[r] ... See full document

22

Multi-domain and multi-task prediction of extraversion and leadership from meeting videos

Multi-domain and multi-task prediction of extraversion and leadership from meeting videos

... use feature analysis and multi-task learning methods in conjunction with the non-verbal features and crowd-sourced annotations from the Video bLOG (VLOG) corpus to perform a ... See full document

14

A Multi task Approach to Learning Multilingual Representations

A Multi task Approach to Learning Multilingual Representations

... to learning multilingual embeddings is to train a multilingual word embedding model that is then used to derive representations for sentences and documents by composition (Hermann and Blun- som, ... See full document

7

Multi Task Active Learning for Linguistic Annotations

Multi Task Active Learning for Linguistic Annotations

... There are two reasons why multi-task AL, and by this, a combined corpus annotated for various tasks, could be of immediate benefit. First, annota- tors working on similar annotation tasks (e.g., con- ... See full document

9

Multi-Task Deep Reinforcement Learning with PopArt

Multi-Task Deep Reinforcement Learning with PopArt

... 2017). Multi-task learning on this plat- form has not been as successful due to large number of envi- ronments, inconsistent dynamics and very different reward ...on multi-task RL in ... See full document

8

Multi Task Learning for Multiple Language Translation

Multi Task Learning for Multiple Language Translation

... sequence learning problem such as speech recognition and machine translation where input and output sequences are of variable ...our multi-task learning framework, the parameters of the gated ... See full document

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