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Ashok Vardhan Makkuva
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2020 – today
- 2024
- [c11]Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael Gastpar:
LASER: Linear Compression in Wireless Distributed Optimization. ICML 2024 - [i16]Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Martin Jaggi, Hyeji Kim, Michael Gastpar:
Attention with Markov: A Framework for Principled Analysis of Transformers via Markov Chains. CoRR abs/2402.04161 (2024) - [i15]Ashok Vardhan Makkuva, Marco Bondaschi, Chanakya Ekbote, Adway Girish, Alliot Nagle, Hyeji Kim, Michael Gastpar:
Local to Global: Learning Dynamics and Effect of Initialization for Transformers. CoRR abs/2406.03072 (2024) - [i14]Adway Girish, Alliot Nagle, Marco Bondaschi, Michael Gastpar, Ashok Vardhan Makkuva, Hyeji Kim:
Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models. CoRR abs/2407.15504 (2024) - [i13]Nived Rajaraman, Marco Bondaschi, Kannan Ramchandran, Michael Gastpar, Ashok Vardhan Makkuva:
Transformers on Markov Data: Constant Depth Suffices. CoRR abs/2407.17686 (2024) - 2023
- [j2]Mohammad Vahid Jamali
, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes. IEEE J. Sel. Areas Inf. Theory 4: 260-275 (2023) - [c10]S. Ashwin Hebbar, Viraj Vivek Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath:
CRISP: Curriculum based Sequential neural decoders for Polar code family. ICML 2023: 12823-12845 - [i12]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes. CoRR abs/2301.06251 (2023) - [i11]Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael C. Gastpar:
LASER: Linear Compression in Wireless Distributed Optimization. CoRR abs/2310.13033 (2023) - 2022
- [c9]S. Ashwin Hebbar
TinyTurbo: Efficient Turbo Decoders on Edge. ISIT 2022: 2797-2802 - [i10]S. Ashwin Hebbar, Rajesh K. Mishra, Sravan Kumar Ankireddy, Ashok Vardhan Makkuva, Hyeji Kim, Pramod Viswanath:
TinyTurbo: Efficient Turbo Decoders on Edge. CoRR abs/2209.15614 (2022) - [i9]S. Ashwin Hebbar, Viraj Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath:
CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family. CoRR abs/2210.00313 (2022) - 2021
- [c8]Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning. ICML 2021: 7368-7378 - [c7]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding. ISIT 2021: 1088-1093 - [i8]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding. CoRR abs/2102.01671 (2021) - [i7]Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
KO codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-learning. CoRR abs/2108.12920 (2021) - 2020
- [c6]Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath:
Learning in Gated Neural Networks. AISTATS 2020: 3338-3348 - [c5]Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee:
Optimal transport mapping via input convex neural networks. ICML 2020: 6672-6681
2010 – 2019
- 2019
- [c4]Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, Pramod Viswanath:
Learning One-hidden-layer Neural Networks under General Input Distributions. AISTATS 2019: 1950-1959 - [c3]Ashok Vardhan Makkuva, Pramod Viswanath, Sreeram Kannan, Sewoong Oh:
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms. ICML 2019: 4304-4313 - [c2]Giulia Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath:
Barracuda: The Power of ℓ-polling in Proof-of-Stake Blockchains. MobiHoc 2019: 351-360 - [i6]Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath:
Learning in Gated Neural Networks. CoRR abs/1906.02777 (2019) - [i5]Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee:
Optimal transport mapping via input convex neural networks. CoRR abs/1908.10962 (2019) - [i4]Giulia Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath:
Barracuda: The Power of 𝓁-polling in Proof-of-Stake Blockchains. CoRR abs/1909.08719 (2019) - 2018
- [j1]Ashok Vardhan Makkuva
Equivalence of Additive-Combinatorial Linear Inequalities for Shannon Entropy and Differential Entropy. IEEE Trans. Inf. Theory 64(5): 3579-3589 (2018) - [i3]Ashok Vardhan Makkuva, Sreeram Kannan, Pramod Viswanath:
Globally Consistent Algorithms for Mixture of Experts. CoRR abs/1802.07417 (2018) - [i2]Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, Pramod Viswanath:
Learning One-hidden-layer Neural Networks under General Input Distributions. CoRR abs/1810.04133 (2018) - 2016
- [c1]Ashok Vardhan Makkuva, Yihong Wu:
On additive-combinatorial affine inequalities for Shannon entropy and differential entropy. ISIT 2016: 1053-1057 - [i1]Ashok Vardhan Makkuva, Yihong Wu:
On additive-combinatorial affine inequalities for Shannon entropy and differential entropy. CoRR abs/1601.07498 (2016)
Coauthor Index
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last updated on 2024-09-04 01:24 CEST by the dblp team
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