🔥 Read our Paper 📚 Chinese Named Entity Recognition Model Based on Multi-Task Learning 🔗 mdpi.com/2076-3417/13/8… 👨‍🔬 by Qin Fang et al. #multitasklearning #Chinesenamedentityrecognition

MtCro: multi-task deep learning framework improves multi-trait genomic prediction of crops Full text: tinyurl.com/59dhzvxa #CropScience #MultitaskLearning #PlantBreeding

#MultitaskLearning Feel free to access the latest SOTA method in Multi-task Optimization. In this work, "GO4Align: group optimization for multi-task alignment," we devise a dynamic grouping mechanism to optimize task losses, aligning the learning progress. 😀

🤗Excited to share that we will be at NeurIPS 2023 in New Orleans to present our spotlight paper “Episodic Multi-Task Learning with Heterogeneous Neural Processes ”. Paper: arxiv.org/abs/2310.18713 Code: github.com/autumn9999/HNPs #NeurIPS2023 #Bayesian #multitasklearning

Multi-Task Architectures: A Comprehensive Guide | @TDataScience #MultiTaskLearning #DeepLearning #MachineLearningArchitecture #AI #DataScience #TowardsDataScience towardsdatascience.com/multi-task-arc…

Please join us virtually at #ICML2023 to check out our papers: 1) Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal 2) BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning #ContinualLearning #MultiTaskLearning #AI

Let's dive into #MultiTaskLearning! 📚🚀We covered the basics in the last post, and now it's time to explore the pros and cons of this approach, along with tips for maximizing its effectiveness. Check it out for more insights: blog.ai.aioz.io/guides/compute… #MachineLearning #AI

Our paper on Multi-Task Structural Learning (MTSL) accepted at #ICML2023! MTSL simultaneously learns the multitask architecture and its parameters, mimicking the structural changes that occur in the brain during learning. 1/4 #MultiTaskLearning #deeplearning #neuroscience

Multi-task learning is a type of machine learning where machines can learn to perform multiple tasks simultaneously, making it a powerful tool for efficiency and performance. #MultiTaskLearning #AI

📢📢📢#MDPIfutureinternet [Highly Cited Papers in 2022] 📌Top 24: Polarity and Subjectivity Detection with #MultitaskLearning and BERT Embedding 🔗see more: mdpi.com/1999-5903/14/7… #polaritydetection #subjectivitydetection #deeplearning #marketintelligence @ComSciMath_Mdpi

tasksource: Structured Dataset Preprocessing Annotations for Frictionless Extreme Multi-Task Learning and Evaluation (480 tasks+ sota encoder) #nlp #multitasklearning reddit.com/r/MachineLearn…

iCYP-MFE: Identifying Human #Cytochrome #P450 Inhibitors Using #MultitaskLearning and Molecular Fingerprint-Embedded Encoding pubs.acs.org/doi/10.1021/ac… #current_issue #JCIM #MachineLearning #DeepLearning

(6/6) Curbing Task Interference using Representation Similarity-Guided Multi-Task Feature Sharing Video: youtube.com/watch?v=9OdpKw… #MultiTaskLearning #DeepLearning

By letting tasks converge on their own, and then switching to a knowledge distillation loss, Amazon scientists' method outperforms existing multitask learning approaches by up to 1.5%. Learn more about their @NAACLmeeting paper. #NAACL2022 #MultitaskLearning

Our new paper where we show the effect of #multitasklearning on #sentimentanalysis #naturallanguageprocessing #senticnet

pubmed.ncbi.nlm.nih.gov/35704370/ When you train your neural network on many related tasks (#EHR time-series prediction tasks) simultaneously, it trains faster and improves the AUROC #medicalinformatics #multitasklearning #deeplearning #machinelearning #healthcare #datascience

Improving ΔΔG Predictions with a Multitask Convolutional Siamese Network #MultitaskLearning #FreeEnergy pubs.acs.org/doi/10.1021/ac… #current_issue #JCIM #MachineLearning #DeepLearning

SUBARU Labではクルマ・人・走行領域・道路標示・信号などを同時に認識させるために、DetectionやSemantic Segmentationといった複数のHeadsが1つのBackboneを共有したMulti-task Networkを開発しています。SUBARU ASURA Netと呼んでいます。 #画像認識 #MultitaskLearning

Mish proposes a new activation function. Compared to ReLU and Swish, Mish offers a smooth loss func landscape (bmvc2020-conference.com/conference/pap…). The optimum region is wider, allowing better generalisation and good for #TransferLearning and #MultitaskLearning. Great work, @DigantaMisra1!

buff.ly/3jQZzWg Another fabulous post by @PinterestEng. This one is about #multitasklearning.