learning task
Learning Task specific Bilexical Embeddings
... the learning algorithm in Section 3 such that the loss is a negative log- likelihood for binary classification, and the regularizer considers the sum of norms of the model ...
11
A model of learning task-specific knowledge for a new task
... next task until we are ...next task? We may choose to handle these problems making them sub- goals, or we may try to find mappings between ‘begin’ and ‘next’ and terms in the scheduling ...to ...
8
Text Segmentation as a Supervised Learning Task
... supervised learning tasks over large amounts of labeled data is highly effective compared to heuristic-based systems or unsupervised algo- rithms (Mikolov et ...supervised learning prob- lem, where a label ...
5
SC LSTM: Learning Task Specific Representations in Multi Task Learning for Sequence Labeling
... Multi-task learning (MTL) has been studied recently for sequence ...target task. Jointly learning multiple tasks in a way that benefit all of them simultaneously can in- crease the utility of ...
11
The learning hierarchy technique: an instructional analysis tool in engineering education
... Keywords: Engineering education, structural design, learning outcomes, learning objectives Learning hierarchies as the products of learning task analyses have been widely used in the pre[r] ...
14
Approaches to learning : the selection and use of learning strategies : a thesis presented in partial fulfilment of the requirements for the degree of Ph D in Human Resource Management at Massey University
... of task demands is surprising for two ...analysing learning task demands for the purpose of instructional design for many ...perceive learning contexts (Hill, 1 98 1 ; Marland & Edwards, 1 ...
298
Multi Task Networks with Universe, Group, and Task Feature Learning
... those task group fea- tures boosts the performance of our unified model on SF and ...– task, task universe, and task group features – the serial architecture for feature learning ...
11
All in one : multi task learning for rumour verification
... classification task is annotated at the tweet level, we use the output from each time step of LSTM, whereas for the tasks of rumour detection and verification, annotated at the thread level, we are only using ...
12
Generalization of auditory sensory and cognitive learning in typically developing children
... [17,32]) learning in children, direct comparison between perceptual and cognitive training on phonological and literacy skills, or even on untrained auditory and cognitive skills, has not previously been ...
18
Few Shot and Zero Shot Learning for Historical Text Normalization
... multi-task learning can lead to significant improvements by exploiting syn- ergies with related datasets, but there has been no systematic study of different multi- task learning ...
11
Allocation of Workers Utilizing Models with Learning, Forgetting, and Various Work Structures
... overlapping task responsibilities [Hopp and Oyen, ...absenteeism, task redundancy, and worker multifunc- tionality on system performance metrics in a descriptive ...identify task redundancy as an ...
70
LANGUAGE LEARNING THROUGH TASK AND ACTIVITIES
... 4. Help them Help you: In general, people aren’t all that good at giving comprehensible input. Usually they either realize you aren’t a native speaker and break into a really loud and generally grammatically incorrect ...
14
Bounds for Linear Multi-Task Learning
... Simultaneous learning of different tasks under some common constraint, often called multi-task learning, has been tested in practice with good results under a variety of different circumstances (see ...
23
Multi Task Learning for Coherence Modeling
... Paragraph sequence (PARSEQ). Lai and Tetreault (2018) implemented a hierarchical neural network consisting of three LSTMs to generate sentence, paragraph and document representations. The network’s architecture is ...
11
Latent Multi-Task Architecture Learning
... Multi-task learning (MTL) in deep neural networks is typ- ically a result of parameter sharing between two networks (of usually the same dimensions) (Caruana ...the task-specific classifier function ...
8
Learning Multi-Task Communication with Message Passing for Sequence Learning
... multi-task learning with neu- ral sequence ...multi-task learning framework in which different tasks can communicate with each other in an effective and interpretable ...multi-task ...
8
Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement Learning
... sequential learning, whenever a trained model, upon training in a new task, moves abruptly in the space of parameters, effectively “forgetting” the original ...second task, these algorithms add an ...
13
Exploring Named Entity Recognition As an Auxiliary Task for Slot Filling in Conversational Language Understanding
... crucial task in the Natural Lan- guage Understanding (NLU) component of a dialogue ...this task rely solely on the domain-specific datasets for ...multi-task learning (MTL) ...auxiliary ...
7
Implementation of Innovative Learning Material to Improve Students Competence on Chemistry
... innovative learning material in the teaching and learning ...a learning package helped the students to complete their routine ...the task had to be submitted as individual ...compulsary ...
14
Identifying beneficial task relations for multi task learning in deep neural networks
... multi-task learning in the ...main task, for instance through a non-uniform drawing of the task con- sidered at each training iteration, or through an adaptation of the learning ...
6