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Provable Benefits of Overparameterization in Model Compression: From
  Double Descent to Pruning Neural Networks

Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks

AAAI Conference on Artificial Intelligence (AAAI), 2020
16 December 2020
Xiangyu Chang
Yingcong Li
Samet Oymak
Christos Thrampoulidis
ArXiv (abs)PDFHTML

Papers citing "Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks"

40 / 40 papers shown
One-Bit Quantization for Random Features Models
One-Bit Quantization for Random Features Models
D. Akhtiamov
Reza Ghane
B. Hassibi
MQ
186
0
0
17 Oct 2025
Information-Theoretic Criteria for Knowledge Distillation in Multimodal Learning
Information-Theoretic Criteria for Knowledge Distillation in Multimodal Learning
Rongrong Xie
Yizhou Xu
Guido Sanguinetti
160
0
0
15 Oct 2025
Optimal Regularization for Performative Learning
Optimal Regularization for Performative Learning
Edwige Cyffers
Alireza Mirrokni
Marco Mondelli
168
0
0
14 Oct 2025
High-dimensional Analysis of Synthetic Data Selection
High-dimensional Analysis of Synthetic Data Selection
Parham Rezaei
Filip Kovačević
Francesco Locatello
Marco Mondelli
212
1
0
09 Oct 2025
Optimal Implicit Bias in Linear Regression
Optimal Implicit Bias in Linear Regression
K. N. Varma
Babak Hassibi
213
1
0
20 Jun 2025
MergeBench: A Benchmark for Merging Domain-Specialized LLMs
MergeBench: A Benchmark for Merging Domain-Specialized LLMs
Yifei He
Siqi Zeng
Yuzheng Hu
Rui Yang
Tong Zhang
Han Zhao
MoMeALM
774
10
0
16 May 2025
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro
Steven Abreu
Jonathan Timcheck
Philipp Stratmann
Andreas Wild
S. Shrestha
399
6
0
03 Feb 2025
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
Simone Bombari
Marco Mondelli
812
7
0
03 Feb 2025
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture
Yikun Hou
Suvrit Sra
A. Yurtsever
378
0
0
27 Jan 2025
Beyond adaptive gradient: Fast-Controlled Minibatch Algorithm for
  large-scale optimization
Beyond adaptive gradient: Fast-Controlled Minibatch Algorithm for large-scale optimization
Corrado Coppola
Lorenzo Papa
Irene Amerini
L. Palagi
ODL
486
0
0
24 Nov 2024
High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws
High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling LawsInternational Conference on Learning Representations (ICLR), 2024
M. E. Ildiz
Halil Alperen Gozeten
Ege Onur Taga
Marco Mondelli
Samet Oymak
608
15
0
24 Oct 2024
Precise asymptotics of reweighted least-squares algorithms for linear
  diagonal networks
Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
Chiraag Kaushik
Justin Romberg
Vidya Muthukumar
244
2
0
04 Jun 2024
Occam Gradient Descent
Occam Gradient Descent
B. N. Kausik
ODLVLM
406
0
0
30 May 2024
Class-wise Activation Unravelling the Engima of Deep Double Descent
Class-wise Activation Unravelling the Engima of Deep Double Descent
Yufei Gu
180
0
0
13 May 2024
Masks, Signs, And Learning Rate Rewinding
Masks, Signs, And Learning Rate Rewinding
Advait Gadhikar
R. Burkholz
269
15
0
29 Feb 2024
Understanding the Role of Optimization in Double Descent
Understanding the Role of Optimization in Double Descent
Chris Yuhao Liu
Jeffrey Flanigan
277
0
0
06 Dec 2023
Efficient Compression of Overparameterized Deep Models through
  Low-Dimensional Learning Dynamics
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics
Soo Min Kwon
Zekai Zhang
Dogyoon Song
Laura Balzano
Qing Qu
339
4
0
08 Nov 2023
Unraveling the Enigma of Double Descent: An In-depth Analysis through
  the Lens of Learned Feature Space
Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space
Yufei Gu
Xiaoqing Zheng
T. Aste
371
5
0
20 Oct 2023
The Quest of Finding the Antidote to Sparse Double Descent
The Quest of Finding the Antidote to Sparse Double Descent
Victor Quétu
Marta Milovanović
350
0
0
31 Aug 2023
DSD$^2$: Can We Dodge Sparse Double Descent and Compress the Neural
  Network Worry-Free?
DSD2^22: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?AAAI Conference on Artificial Intelligence (AAAI), 2023
Victor Quétu
Enzo Tartaglione
412
6
0
02 Mar 2023
Can we avoid Double Descent in Deep Neural Networks?
Can we avoid Double Descent in Deep Neural Networks?International Conference on Information Photonics (ICIP), 2023
Victor Quétu
Enzo Tartaglione
AI4CE
340
2
0
26 Feb 2023
Precise Asymptotic Analysis of Deep Random Feature Models
Precise Asymptotic Analysis of Deep Random Feature ModelsAnnual Conference Computational Learning Theory (COLT), 2023
David Bosch
Ashkan Panahi
B. Hassibi
385
21
0
13 Feb 2023
Strong inductive biases provably prevent harmless interpolation
Strong inductive biases provably prevent harmless interpolationInternational Conference on Learning Representations (ICLR), 2023
Michael Aerni
Marco Milanta
Konstantin Donhauser
Fanny Yang
299
10
0
18 Jan 2023
Why Random Pruning Is All We Need to Start Sparse
Why Random Pruning Is All We Need to Start SparseInternational Conference on Machine Learning (ICML), 2022
Advait Gadhikar
Sohom Mukherjee
R. Burkholz
355
31
0
05 Oct 2022
Deep Double Descent via Smooth Interpolation
Deep Double Descent via Smooth Interpolation
Matteo Gamba
Erik Englesson
Mårten Björkman
Hossein Azizpour
712
13
0
21 Sep 2022
Overparameterization from Computational Constraints
Overparameterization from Computational ConstraintsNeural Information Processing Systems (NeurIPS), 2022
Sanjam Garg
S. Jha
Saeed Mahloujifar
Mohammad Mahmoody
Mingyuan Wang
237
3
0
27 Aug 2022
Sparse Double Descent: Where Network Pruning Aggravates Overfitting
Sparse Double Descent: Where Network Pruning Aggravates OverfittingInternational Conference on Machine Learning (ICML), 2022
Zhengqi He
Zeke Xie
Quanzhi Zhu
Zengchang Qin
342
35
0
17 Jun 2022
Deep Architecture Connectivity Matters for Its Convergence: A
  Fine-Grained Analysis
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained AnalysisNeural Information Processing Systems (NeurIPS), 2022
Wuyang Chen
Wei-Ping Huang
Xinyu Gong
Boris Hanin
Zinan Lin
296
9
0
11 May 2022
Random Features Model with General Convex Regularization: A Fine Grained
  Analysis with Precise Asymptotic Learning Curves
Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning CurvesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
David Bosch
Ashkan Panahi
Ayça Özçelikkale
Devdatt Dubhash
MLT
350
3
0
06 Apr 2022
Provable and Efficient Continual Representation Learning
Provable and Efficient Continual Representation Learning
Yingcong Li
Mingchen Li
M. Salman Asif
Samet Oymak
CLL
293
16
0
03 Mar 2022
Towards Sample-efficient Overparameterized Meta-learning
Towards Sample-efficient Overparameterized Meta-learningNeural Information Processing Systems (NeurIPS), 2022
Yue Sun
Adhyyan Narang
Halil Ibrahim Gulluk
Samet Oymak
Maryam Fazel
BDL
194
25
0
16 Jan 2022
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of
  Overparameterized Machine Learning
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning
Yehuda Dar
Vidya Muthukumar
Richard G. Baraniuk
310
79
0
06 Sep 2021
How much pre-training is enough to discover a good subnetwork?
How much pre-training is enough to discover a good subnetwork?
Cameron R. Wolfe
Fangshuo Liao
Qihan Wang
Junhyung Lyle Kim
Anastasios Kyrillidis
315
4
0
31 Jul 2021
Spectral Pruning for Recurrent Neural Networks
Spectral Pruning for Recurrent Neural NetworksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Takashi Furuya
Kazuma Suetake
K. Taniguchi
Hiroyuki Kusumoto
Ryuji Saiin
Tomohiro Daimon
212
4
0
23 May 2021
Generalization Guarantees for Neural Architecture Search with
  Train-Validation Split
Generalization Guarantees for Neural Architecture Search with Train-Validation SplitInternational Conference on Machine Learning (ICML), 2021
Samet Oymak
Mingchen Li
Mahdi Soltanolkotabi
AI4CEOOD
307
20
0
29 Apr 2021
Lottery Jackpots Exist in Pre-trained Models
Lottery Jackpots Exist in Pre-trained ModelsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Yuxin Zhang
Mingbao Lin
Yan Wang
Jiayi Ji
Rongrong Ji
485
19
0
18 Apr 2021
Label-Imbalanced and Group-Sensitive Classification under
  Overparameterization
Label-Imbalanced and Group-Sensitive Classification under OverparameterizationNeural Information Processing Systems (NeurIPS), 2021
Ganesh Ramachandra Kini
Orestis Paraskevas
Samet Oymak
Christos Thrampoulidis
580
115
0
02 Mar 2021
Distilling Double Descent
Distilling Double Descent
Andrew Cotter
A. Menon
Harikrishna Narasimhan
A. S. Rawat
Sashank J. Reddi
Yichen Zhou
261
7
0
13 Feb 2021
Binary Classification of Gaussian Mixtures: Abundance of Support
  Vectors, Benign Overfitting and Regularization
Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting and RegularizationSIAM Journal on Mathematics of Data Science (SIMODS), 2020
Ke Wang
Christos Thrampoulidis
541
34
0
18 Nov 2020
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization
  is Sufficient
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is SufficientNeural Information Processing Systems (NeurIPS), 2020
Ankit Pensia
Shashank Rajput
Alliot Nagle
Harit Vishwakarma
Dimitris Papailiopoulos
429
115
0
14 Jun 2020
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