Gradient surgery for multi-task learning
WebWe propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. On a series of … WebGradient Surgery for Multi-Task Learning. 226 0 2024-11-17 09:52:00 ...
Gradient surgery for multi-task learning
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WebWe propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. On a series of challenging multi-task supervised and multi-task RL problems, this approach leads to substantial gains in efficiency and performance. http://arxiv-export3.library.cornell.edu/pdf/2001.06782v1
WebJan 5, 2024 · The objective of multi-task learning (MTL) [ 3, 26] is to develop methods that can tackle a large variety of tasks within a single model. MTL has multiple practical benefits. First, learning shared parameters across multiple tasks leads to representations that can be more data-efficient to train and also generalize better to unseen data.
WebWe propose a form of gradient surgery that projects the gradient of a task onto the normal plane of the gradient of any other task that has a conflicting gradient. On a series of challenging multi-task supervised and multi-task reinforcement learning problems, we find that this approach leads to substantial gains in efficiency and performance. WebMDL-NAS: A Joint Multi-domain Learning framework for Vision Transformer Shiguang Wang · TAO XIE · Jian Cheng · Xingcheng ZHANG · Haijun Liu Independent Component Alignment for Multi-Task Learning Dmitry Senushkin · Nikolay Patakin · Arsenii Kuznetsov · Anton Konushin Revisiting Prototypical Network for Cross Domain Few-Shot Learning
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WebDec 6, 2024 · We propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. On a series of challenging multi-task supervised and multi-task RL problems, this approach leads to substantial gains in efficiency and performance. Further, it is model-agnostic and … how do you pronounce humiraWebGradient Surgery for Multi-Task Learning. Tianhe Yu1 , Saurabh Kumar1 , Abhishek Gupta2 , Sergey Levine2 , Karol Hausman3 , Chelsea Finn1 Stanford University1 , UC Berkeley2 , Robotics at Google3 [email protected] arXiv:2001.06782v4 [cs.LG] 22 Dec 2024. Abstract how do you pronounce huluWebent surgery that projects a task’s gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. On a series of challenging multi-task … how do you pronounce huong in vietnameseWebSummary and Contributions: This paper proposed projecting conflicting gradients (PCGrad) to solve the problem of conflicting gradient in multitask learning. Experiments on computer vision tasks and reinforcement learning tasks verifies the effectiveness of … phone number cellularWebMulti-task learning has emerged as a promising approach for sharing structure across multiple tasks to enable more efficient learning. However, the multi-task setting presents a number of optimiza- ... Figure 1: Visualization of gradient surgery’s effect on a 2D multi-task optimization problem. (a) A multi-task objective landscape. (b) & (c ... phone number cellular outfitterWebWe identify a set of three conditions of the multi-task optimization landscape that cause detrimental gradient interference, and develop a simple yet general approach, projecting conflicting gradients (PCGrad), … phone number central bank boone countyWeb我们提出了一种梯度手术（Gradient Surgery）的形式，将任务的梯度投影到具有冲突梯度的任何其他任务的梯度的法线平面上。 在一系列具有挑战性的多任务监督和多任务 RL 问 … phone number cell phone