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• Reinforcement Learning of Theorem Proving
  ...rning has been used to replace such heuristics and improve the performance of ATPs. ...esults in a 42.1% performance increase compared to the base prover(without learning). ...
  20 KB (3,127 words) - 20:45, 10 December 2018

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• stat946F18
  ...h neural networks.||[http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf Paper] || [[https://wiki.math.uwaterloo.ca/statwik ...t Singh Minhas || 4 || End-to-end Active Object Tracking via Reinforcement Learning || [http://proceedings.mlr.press/v80/luo18a/luo18a.pdf Paper] || [https://w ...
  14 KB (1,851 words) - 03:22, 2 December 2018
• Reinforcement Learning of Theorem Proving
  ...rning has been used to replace such heuristics and improve the performance of ATPs. ...esults in a 42.1% performance increase compared to the base prover(without learning). ...
  20 KB (3,127 words) - 20:45, 10 December 2018
• GradientLess Descent
  Depending on the nature of <math display="inline">f</math>, different settings may be considered: ...practice; for instance, they make special appearances in the reinforcement learning literature. ...
  11 KB (1,754 words) - 22:06, 9 December 2020
• F18-STAT946-Proposal
  ...:''' We use paper cups to make a string phone and talk with friends while learning about sound waves with this science project. (Explain your project in one o ...le:''' Algorithmic Analysis and Improvements in Multi-Agent Reinforcement Learning in Partially Observable Settings ...
  17 KB (2,400 words) - 15:50, 14 December 2018
• stat946w18/Self Normalizing Neural Networks
  ...k and recurrent network structures. Most data science competitions outside of these domains are still outperformed by algorithms such as gradient boostin ...perty and thus suffer from high variance in training errors, which hinders learning. Furthermore, the aforementioned normalization techniques involve adding ex ...
  45 KB (6,836 words) - 23:26, 20 April 2018