עקוב אחר
Lukas Balles
Lukas Balles
Aleph Alpha
כתובת אימייל מאומתת בדומיין aleph-alpha.com - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation‏
A Ranjan, V Jampani, L Balles, K Kim, D Sun, J Wulff, MJ Black‏
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019‏
7202019
Limitations of the empirical fisher approximation for natural gradient descent‏
F Kunstner, P Hennig, L Balles‏
Advances in neural information processing systems 32, 2019‏
2392019
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients‏
L Balles, P Hennig‏
Proceedings of the 35th International Conference on Machine Learning (ICML …, 2018‏
2012018
Coupling Adaptive Batch Sizes with Learning Rates‏
L Balles, J Romero, P Hennig‏
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial …, 2017‏
1422017
Early stopping without a validation set‏
M Mahsereci, L Balles, C Lassner, P Hennig‏
arXiv preprint arXiv:1703.09580, 2017‏
1212017
DeepOBS: A Deep Learning Optimizer Benchmark Suite‏
F Schneider, L Balles, P Hennig‏
Seventh International Conference on Learning Representations (ICLR), 2019‏
782019
PASHA: Efficient HPO and NAS with progressive resource allocation‏
O Bohdal, L Balles, M Wistuba, B Ermis, C Archambeau, G Zappella‏
arXiv preprint arXiv:2207.06940, 2022‏
222022
The Geometry of Sign Gradient Descent‏
L Balles, F Pedregosa, N Le Roux‏
arXiv preprint arXiv:2002.08056, 2020‏
222020
Continual learning with low rank adaptation‏
M Wistuba, PT Sivaprasad, L Balles, G Zappella‏
arXiv preprint arXiv:2311.17601, 2023‏
132023
Self-tuning stochastic optimization with curvature-aware gradient filtering‏
RTQ Chen, D Choi, L Balles, D Duvenaud, P Hennig‏
PMLR, 2020‏
82020
u-P: The Unit-Scaled Maximal Update Parametrization‏
C Blake, C Eichenberg, J Dean, L Balles, LY Prince, B Deiseroth, ...‏
arXiv preprint arXiv:2407.17465, 2024‏
72024
Renate: A library for real-world continual learning‏
M Wistuba, M Ferianc, L Balles, C Archambeau, G Zappella‏
arXiv preprint arXiv:2304.12067, 2023‏
62023
Gradient-matching coresets for rehearsal-based continual learning‏
L Balles, G Zappella, C Archambeau‏
arXiv preprint arXiv:2203.14544, 2022‏
62022
Holographic and other point set distances for machine learning‏
L Balles, T Fischbacher‏
62019
Automating stochastic optimization with gradient variance estimates‏
L Balles, M Mahsereci, P Hennig‏
ICML AutoML Workshop, 13, 2017‏
42017
Choice of peft technique in continual learning: Prompt tuning is not all you need‏
M Wistuba, PT Sivaprasad, L Balles, G Zappella‏
arXiv preprint arXiv:2406.03216, 2024‏
22024
On the choice of learning rate for local SGD‏
L Balles, C Archambeau‏
Transactions on Machine Learning Research, 2024‏
22024
Gradient-matching coresets for continual learning‏
L Balles, G Zappella, C Archambeau‏
arXiv preprint arXiv:2112.05025, 2021‏
22021
Hierarchical Autoregressive Transformers: Combining Byte-and Word-Level Processing for Robust, Adaptable Language Models‏
P Neitemeier, B Deiseroth, C Eichenberg, L Balles‏
arXiv preprint arXiv:2501.10322, 2025‏
2025
Continual machine learning in a provider network‏
G Zappella, LS Balles, B Ermis, M Wistuba, CP Archambeau‏
US Patent App. 17/937,319, 2024‏
2024
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מאמרים 1–20