Követés
Chen Liang
Chen Liang
Google DeepMind, previously Google Brain
E-mail megerősítve itt: google.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Gemini: a family of highly capable multimodal models
G team
https://storage.googleapis.com/deepmind-media/gemini/gemini_1_report.pdf, 2023
32082023
Carbon emissions and large neural network training
D Patterson, J Gonzalez, Q Le, C Liang, LM Munguia, D Rothchild, D So, ...
arXiv preprint arXiv:2104.10350, 2021
9112021
The evolved transformer
D So, C Liang, Q Le
International conference on machine learning, 5877-5886, 2019
5612019
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
C Liang, J Berant, Q Le, KD Forbus, N Lao
ACL 2017, 55th Annual Meeting of the Association for Computational …, 2017
4772017
Symbolic Discovery of Optimization Algorithms
X Chen*, C Liang*, D Huang, E Real, K Wang, Y Liu, H Pham, X Dong, ...
arXiv preprint arXiv:2302.06675, 2023
4752023
Automl-zero: Evolving machine learning algorithms from scratch
E Real*, C Liang*, D So, Q Le
International Conference on Machine Learning, 8007-8019, 2020
3592020
The carbon footprint of machine learning training will plateau, then shrink
D Patterson, J Gonzalez, U Hölzle, Q Le, C Liang, LM Munguia, ...
Computer 55 (7), 18-28, 2022
3482022
Memory augmented policy optimization for program synthesis and semantic parsing
C Liang, M Norouzi, J Berant, QV Le, N Lao
Advances in Neural Information Processing Systems 31, 2018
174*2018
Definition modeling: Learning to define word embeddings in natural language
T Noraset, C Liang, L Birnbaum, D Downey
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
1462017
Neural symbolic reader: Scalable integration of distributed and symbolic representations for reading comprehension
X Chen, C Liang, AW Yu, D Zhou, D Song, QV Le
International Conference on Learning Representations, 2019
1262019
Learning to generalize from sparse and underspecified rewards
R Agarwal, C Liang, D Schuurmans, M Norouzi
International conference on machine learning, 130-140, 2019
1112019
Compositional generalization via neural-symbolic stack machines
X Chen, C Liang, AW Yu, D Song, D Zhou
Advances in Neural Information Processing Systems 33, 1690-1701, 2020
1102020
Pyglove: Symbolic programming for automated machine learning
D Peng, X Dong, E Real, M Tan, Y Lu, G Bender, H Liu, A Kraft, C Liang, ...
Advances in Neural Information Processing Systems 33, 96-108, 2020
342020
Learning plausible inferences from semantic web knowledge by combining analogical generalization with structured logistic regression
C Liang, K Forbus
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
242015
Representation and computation in cognitive models
KD Forbus, C Liang, I Rabkina
Topics in cognitive science 9 (3), 694-718, 2017
222017
Learning Paraphrase Identification with Structural Alignment
C Liang, P Paritosh, V Rajendran, KD Forbus
IJCAI 2016, 2016
212016
Constructing hierarchical concepts via analogical generalization
C Liang, K Forbus
Proceedings of the Annual Meeting of the Cognitive Science Society 36 (36), 2014
112014
Hyperscale hardware optimized neural architecture search
S Li, G Andersen, T Chen, L Cheng, J Grady, D Huang, QV Le, A Li, X Li, ...
Proceedings of the 28th ACM International Conference on Architectural …, 2023
82023
Neural question answering system
N Lao, C Liang, QV Le, J Blitzer
US Patent App. 16/176,961, 2019
72019
Communication efficient distributed training with distributed lion
B Liu, L Wu, L Chen, K Liang, J Zhu, C Liang, R Krishnamoorthi, Q Liu
arXiv preprint arXiv:2404.00438, 2024
42024
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Cikkek 1–20