Követés
Christopher A. Choquette-Choo
Christopher A. Choquette-Choo
További nevekChristopher Choquette-Choo, Christopher Choquette
Google DeepMind
E-mail megerősítve itt: google.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805, 2023
34172023
PaLM 2 Technical Report
R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ...
Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vladimir Feinberg, Fangxiaoyu …, 2023
16932023
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ...
arXiv preprint arXiv:2403.05530, 2024
13052024
Gemma: Open models based on gemini research and technology
G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ...
arXiv preprint arXiv:2403.08295, 2024
11032024
Machine unlearning
L Bourtoule, V Chandrasekaran, CA Choquette-Choo, H Jia, A Travers, ...
42nd IEEE Symposium on Security and Privacy, 2021
9802021
Label-Only Membership Inference Attacks
CA Choquette-Choo, F Tramer, N Carlini, N Papernot
38th International Conference on Machine Learning, 2021
5702021
Gemma 2: Improving open language models at a practical size
G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ...
arXiv preprint arXiv:2408.00118, 2024
5282024
Scalable extraction of training data from (production) language models
M Nasr, N Carlini, J Hayase, M Jagielski, AF Cooper, D Ippolito, ...
arXiv preprint arXiv:2311.17035, 2023
3332023
Entangled watermarks as a defense against model extraction
H Jia, CA Choquette-Choo, V Chandrasekaran, N Papernot
30th USENIX security symposium (USENIX Security 21), 1937-1954, 2021
2982021
Are aligned neural networks adversarially aligned?
N Carlini, M Nasr, CA Choquette-Choo, M Jagielski, I Gao, PWW Koh, ...
Advances in Neural Information Processing Systems 36, 61478-61500, 2023
2872023
Poisoning web-scale training datasets is practical
N Carlini, M Jagielski, CA Choquette-Choo, D Paleka, W Pearce, ...
2024 IEEE Symposium on Security and Privacy (SP), 407-425, 2024
2062024
Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy
D Ippolito, F Tramèr, M Nasr, C Zhang, M Jagielski, K Lee, CC Choo, ...
Proceedings of the 16th International Natural Language Generation Conference …, 2023
152*2023
Proof-of-Learning: Definitions and Practice
H Jia, M Yaghini, CA Choquette-Choo, N Dullerud, A Thudi, ...
42nd IEEE Symposium on Security and Privacy, 2021
1142021
Madlad-400: A multilingual and document-level large audited dataset
S Kudugunta, I Caswell, B Zhang, X Garcia, CA Choquette-Choo, K Lee, ...
Advances in Neural Information Processing Systems 36, 2024
1112024
Federated learning of gboard language models with differential privacy
Z Xu, Y Zhang, G Andrew, CA Choquette-Choo, P Kairouz, HB McMahan, ...
arXiv preprint arXiv:2305.18465, 2023
872023
Palm 2 technical report. arXiv 2023
R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ...
arXiv preprint arXiv:2305.10403, 0
87
Codegemma: Open code models based on gemma
CG Team, AJ Hartman, A Hu, CA Choquette-Choo, H Zhao, J Fine, J Hui, ...
URL https://storage. googleapis. com/deepmind-media/gemma/codegemma_report. pdf, 0
84*
The fundamental price of secure aggregation in differentially private federated learning
WN Chen, CAC Choo, P Kairouz, AT Suresh
International Conference on Machine Learning, 3056-3089, 2022
732022
CaPC Learning: Confidential and Private Collaborative Learning
CA Choquette-Choo, N Dullerud, A Dziedzic, Y Zhang, S Jha, N Papernot, ...
9th International Conference on Learning Representations, 2021
732021
Multi-epoch matrix factorization mechanisms for private machine learning
CA Choquette-Choo, HB McMahan, K Rush, A Thakurta
40th International Conference on Machine Learning 202, 5924-5963, 2023
432023
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