chi jin: bellman eluder dimension: new rich classes of rl problems and sample-efficient algorithms
Published 3 years ago • 644 plays • Length 1:02:30Download video MP4
Download video MP3
Similar videos
-
1:44
schmalz videocast #11 – vision & handling set 3d-r
-
1:00:54
rl theory seminar: chi jin
-
28:05
provably efficient reinforcement learning with linear function approximation - chi jin
-
49:43
big data on smallish machines
-
1:02:32
rl theory seminar: xinyi chen
-
1:04:49
06 – latent variable energy based models (lv-ebms), training
-
2:00:19
the tiny model revolution with ronen eldan and yuanzhi li of microsoft research
-
1:54:44
08l – self-supervised learning and variational inference
-
19:49
deep learning vs machine learning in r
-
1:07:26
rl theory seminar: max simchowitz
-
26:37
e-commerce anomaly detection: a bayesian semi-supervised tensor.... by anil yelundur
-
1:20:37
rl theory seminar: nan jiang
-
1:29:57
analytic methods for supervised learning ii
-
18:15
next generation hmi development - by david aberl
-
3:01
learning hierarchical information flow with recurrent neural modules
-
2:21
introducing epsrc engineering net zero: professor dame lynn gladden
-
43:51
is q-learning provably efficient?
-
1:03:13
rl theory seminar: zhuoran yang
-
5:12
scmultisim: simulation of multi-modality single cell data... - hechen li - rsg - rsgdream 2022
-
11:10
heavy metal neuroscience: protein-based, single-cell analysis of neural cells
-
1:19:18
dlrlss 2019 - sample efficient rl - harm van seijen
-
33:43
generalizing the projected bellman error objective for nonlinear value estimation