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Multitask Diļ¬usion Adaptation over Networks
The dataset used in the paper is a simulated multi-task nonlinear problem. -
Multitask Representation Learning in Linear MDPs
The dataset is used for multitask representation learning in linear MDPs. It contains 80 different tasks, each with a different destination position, fire configuration, and... -
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning
Physics-informed machine learning (PIML) as a means of solving partial differential equations (PDE) has garnered much attention in the Computational Science and Engineering... -
Multitask dataset of product reviews
The dataset used in the paper is the Multitask dataset of product reviews, containing customer reviews for 957 Amazon products from the "Amazon product data" (McAuley et al.,... -
Sparse Diffusion Policy: A Sparse, Reusable, and Flexible Policy for Robot Le...
The Sparse Diffusion Policy (SDP) framework, which integrates Mixture of Experts (MoE) layers into the diffusion policy. -
JMMLU: Japanese Massive Multitask Language Understanding Benchmark
The authors constructed the Japanese Massive Multitask Language Understanding Benchmark (JMMLU) by translating MMLU and adding tasks related to Japanese culture. -
Decentralized Multitask Learning
The dataset used in the paper is a network of agents with heterogeneous objectives and data. -
Multitask Learning and Benchmarking with Clinical Time Series Data
The dataset for the proposed multitask learning approach, containing clinical time series data. -
Multitask Character Classification Benchmark
The Multitask Character Classification Benchmark consists of 8 publicly available character classification tasks. -
muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Mul...
The proposed method uses the layers of a pretrained deep neural network as building blocks to construct an ML system that can jointly solve an arbitrary number of tasks.
