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Exploration is Harder than Prediction: Cryptographically Separating
  Reinforcement Learning from Supervised Learning

Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning

4 April 2024
Noah Golowich
Ankur Moitra
Dhruv Rohatgi
    OffRL
ArXivPDFHTML

Papers citing "Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning"

4 / 4 papers shown
Title
Can we hop in general? A discussion of benchmark selection and design
  using the Hopper environment
Can we hop in general? A discussion of benchmark selection and design using the Hopper environment
C. Voelcker
Marcel Hussing
Eric Eaton
OffRL
18
3
0
11 Oct 2024
Exploratory Preference Optimization: Harnessing Implicit
  Q*-Approximation for Sample-Efficient RLHF
Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF
Tengyang Xie
Dylan J. Foster
Akshay Krishnamurthy
Corby Rosset
Ahmed Hassan Awadallah
Alexander Rakhlin
36
32
0
31 May 2024
Oracle-Efficient Reinforcement Learning for Max Value Ensembles
Oracle-Efficient Reinforcement Learning for Max Value Ensembles
Marcel Hussing
Michael Kearns
Aaron Roth
S. B. Sengupta
Jessica Sorrell
24
0
0
27 May 2024
On Learning Parities with Dependent Noise
On Learning Parities with Dependent Noise
Noah Golowich
Ankur Moitra
Dhruv Rohatgi
23
1
0
17 Apr 2024
1