Results 51 to 60 of about 5,803,394 (295)
Collaborative Online Multitask Learning
IEEE Transactions on Knowledge and Data Engineering, 2014 We study the problem of online multitask learning for solving multiple related classification tasks in parallel, aiming at classifying every sequence of data received by each task accurately and efficiently. One practical example of online multitask learning is the micro-blog sentiment detection on a group of users, which classifies micro-blog posts ...
LI, Guangxia +4 more
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Multitask Learning of Time-Frequency CNN for Sound Source Localization
IEEE Access, 2019 Sound source localization (SSL) is an important technique for many audio processing systems, such as speech enhancement/recognition and human-robot interaction.
Cheng Pang, Hong Liu, Xiaofei Li
doaj +1 more source
Distributed Multitask Learning
, 2015 We consider the problem of distributed multi-task learning, where each machine learns a separate, but related, task. Specifically, each machine learns a linear predictor in high-dimensional space,where all tasks share the same small support. We present a communication-efficient estimator based on the debiased lasso and show that it is comparable with ...
Wang, Jialei +2 more
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Confidence Weighted Multitask Learning
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 Traditional online multitask learning only utilizes the firstorder information of the datastream. To remedy this issue, we propose a confidence weighted multitask learning algorithm, which maintains a Gaussian distribution over each task model to guide online learning process.
Yang, Peng +3 more
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Deep Learning-Enabled Multitask System for Exercise Recognition and Counting
Multimodal Technologies and Interaction, 2021 Exercise is a prevailing topic in modern society as more people are pursuing a healthy lifestyle. Physical activities provide significant benefits to human well-being from the inside out.
Qingtian Yu +3 more
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A Principled Approach for Learning Task Similarity in Multitask Learning
, 2019 Multitask learning aims at solving a set of related tasks simultaneously, by exploiting the shared knowledge for improving the performance on individual tasks.
Abbasi, Mahdieh +4 more
core +1 more source
Distral: Robust Multitask Reinforcement Learning
, 2017 Most deep reinforcement learning algorithms are data inefficient in complex and rich environments, limiting their applicability to many scenarios. One direction for improving data efficiency is multitask learning with shared neural network parameters, where efficiency may be improved through transfer across related tasks.
Teh, YW +7 more
openaire +3 more sources
Identification of Social-Media Platform of Videos through the Use of Shared Features
Journal of Imaging, 2021 Videos have become a powerful tool for spreading illegal content such as military propaganda, revenge porn, or bullying through social networks. To counter these illegal activities, it has become essential to try new methods to verify the origin of ...
Luca Maiano +3 more
doaj +1 more source
Learning Representations of Emotional Speech with Deep Convolutional Generative Adversarial Networks
, 2017 Automatically assessing emotional valence in human speech has historically been a difficult task for machine learning algorithms. The subtle changes in the voice of the speaker that are indicative of positive or negative emotional states are often ...
Chang, Jonathan, Scherer, Stefan
core +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
Advanced Robotics Research, EarlyView.BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source