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2020 – today
- 2024
[c6]Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley, Charlie Blake, Carlo Luschi, Douglas Orr:
SparQ Attention: Bandwidth-Efficient LLM Inference. ICML 2024- [i17]Alexander Mathiasen, Hatem Helal, Paul Balanca, Adam Krzywaniak, Ali Parviz, Frederik Hvilshøj, Blazej Banaszewski, Carlo Luschi, Andrew William Fitzgibbon:
Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory. CoRR abs/2402.04030 (2024) - [i16]Paul Balanca, Sam Hosegood, Carlo Luschi, Andrew W. Fitzgibbon:
Scalify: scale propagation for efficient low-precision LLM training. CoRR abs/2407.17353 (2024) - [i15]Charlie Blake, Constantin Eichenberg, Josef Dean, Lukas Balles, Luke Y. Prince, Björn Deiseroth, Andrés Felipe Cruz-Salinas, Carlo Luschi, Samuel Weinbach, Douglas Orr:
u-μP: The Unit-Scaled Maximal Update Parametrization. CoRR abs/2407.17465 (2024) - [i14]Alberto Cattaneo, Stephen Bonner, Thomas Martynec, Carlo Luschi, Ian P. Barrett, Daniel Justus:
The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models. CoRR abs/2409.04103 (2024) - 2023
- [c5]Charlie Blake, Douglas Orr, Carlo Luschi:
Unit Scaling: Out-of-the-Box Low-Precision Training. ICML 2023: 2548-2576 - [c4]Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters:
Generating QM1B with PySCFIPU. NeurIPS 2023 - [i13]Charlie Blake, Douglas Orr, Carlo Luschi:
Unit Scaling: Out-of-the-Box Low-Precision Training. CoRR abs/2303.11257 (2023) - [i12]Sergio P. Perez, Yan Zhang, James Briggs, Charlie Blake, Josh Levy-Kramer, Paul Balanca, Carlo Luschi, Stephen Barlow, Andrew William Fitzgibbon:
Training and inference of large language models using 8-bit floating point. CoRR abs/2309.17224 (2023) - [i11]Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters:
Generating QM1B with PySCFIPU. CoRR abs/2311.01135 (2023) - [i10]Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley, Charlie Blake, Carlo Luschi, Douglas Orr:
SparQ Attention: Bandwidth-Efficient LLM Inference. CoRR abs/2312.04985 (2023) - 2022
- [i9]Badreddine Noune, Philip Jones, Daniel Justus, Dominic Masters, Carlo Luschi:
8-bit Numerical Formats for Deep Neural Networks. CoRR abs/2206.02915 (2022) - [i8]Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr, Jérôme Maloberti, Zhenying Liu, Thorin Farnsworth, Andrew W. Fitzgibbon, Blazej Banaszewski, Carlo Luschi:
BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph Completion. CoRR abs/2211.12281 (2022) - 2021
- [c3]Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi:
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence. NeurIPS 2021: 16990-17006 - [i7]Dominic Masters, Antoine Labatie, Zach Eaton-Rosen, Carlo Luschi:
Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training. CoRR abs/2106.03640 (2021) - [i6]Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi:
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence. CoRR abs/2106.03743 (2021) - [i5]Ivan Chelombiev, Daniel Justus, Douglas Orr, Anastasia Dietrich, Frithjof Gressmann, Alexandros Koliousis, Carlo Luschi:
GroupBERT: Enhanced Transformer Architecture with Efficient Grouped Structures. CoRR abs/2106.05822 (2021) - [i4]Anastasia Dietrich, Frithjof Gressmann, Douglas Orr, Ivan Chelombiev, Daniel Justus, Carlo Luschi:
Towards Structured Dynamic Sparse Pre-Training of BERT. CoRR abs/2108.06277 (2021) - 2020
- [c2]Frithjof Gressmann, Zach Eaton-Rosen, Carlo Luschi:
Improving Neural Network Training in Low Dimensional Random Bases. NeurIPS 2020 - [i3]Frithjof Gressmann, Zach Eaton-Rosen, Carlo Luschi:
Improving Neural Network Training in Low Dimensional Random Bases. CoRR abs/2011.04720 (2020) - [i2]Michael Laskin, Luke Metz, Seth Nabarrao, Mark Saroufim, Badreddine Noune, Carlo Luschi, Jascha Sohl-Dickstein, Pieter Abbeel:
Parallel Training of Deep Networks with Local Updates. CoRR abs/2012.03837 (2020)
2010 – 2019
- 2018
- [i1]Dominic Masters, Carlo Luschi:
Revisiting Small Batch Training for Deep Neural Networks. CoRR abs/1804.07612 (2018)
2000 – 2009
- 2005
- [j5]Carlo Luschi, Bernard Mulgrew
:
Estimation of the output error statistics of space-time equalization in an antenna array EGPRS receiver with soft-decision decoding. IEEE Trans. Wirel. Commun. 4(4): 1377-1382 (2005) - 2003
- [j4]Carlo Luschi, Bernard Mulgrew:
Nonparametric trellis equalization in the presence of non-Gaussian interference. IEEE Trans. Commun. 51(2): 229-239 (2003) - 2000
- [j3]Carlo Luschi, Magnus Sandell, Paul Strauch, Jian-Jun Wu, Costel Ilas, Ping-Wen Ong, Romain Baeriswyl, Frederic Battaglia, Spyros Karageorgis, Ran-Hong Yan:
Advanced signal-processing algorithms for energy-efficient wireless communications. Proc. IEEE 88(10): 1633-1650 (2000)
1990 – 1999
- 1999
- [c1]Paul Strauch, Carlo Luschi, Magnus Sandell, Ran Yan:
Low complexity source controlled channel decoding in a GSM system. ICASSP 1999: 2571-2574 - 1996
- [j2]Franco Guglielmi, Carlo Luschi, Arnaldo Spalvieri:
Joint clock recovery and baseband combining for the diversity radio channel. IEEE Trans. Commun. 44(1): 114-117 (1996) - 1995
- [j1]Franco Guglielmi, Carlo Luschi, Arnaldo Spalvieri:
Joint Clock Recovery and Baseband Combining for the Diversity Radio Channel. IEEE Trans. Commun. 43(12): 3101 (1995)
Coauthor Index
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last updated on 2024-10-10 22:19 CEST by the dblp team
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