AMTL 2019

Overview Driven by progress in deep learning, the machine learning community is now able to tackle increasingly more complex problems—ranging from multi-modal reasoning to dexterous robotic manipulation—all of which typically involve solving nontrivial combinations of tasks. We believe that designing adaptive models and algorithms that can efficiently learn, master, and combine multiple tasks is the next frontier. Establishing connections between approaches developed for seemingly different pro

3 mentions: @atalwalkar@pliang279@DSakya
Date: 2019/06/12 17:16

Referring Tweets

@atalwalkar Exciting work by @khodakmoments on theory for gradient-based meta learning (think MAML, Reptile, or even FedAvg) at #ICML2019. Check out Misha's poster tonight (Poster 253), as well as my talk at the AMTL workshop (https://t.co/AGuZPWGyyK) on Saturday at 1:45pm.
@DSakya Presenting two papers at #icml2019 workshops - “Lifelong learning with online leverage score sampling” at https://t.co/arwVQJPILz & “Model-based deep RL for financial portfolio optimization” at https://t.co/2KxGOOwWJw If you are attending, please stop by to discuss.
@pliang279 2. Adaptive and Multitask Learning: Algorithms & Systems https://t.co/OXnENWJW0d Sat Jun 15th 08:30 AM - 06:00 PM @ Seaside Ballroom @eaplatanios @alshedivat @mldcmu @LTIatCMU

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