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Learning the Pareto Front with Hypernetworks

Learning the Pareto Front with Hypernetworks

8 October 2020
Aviv Navon
Aviv Shamsian
Gal Chechik
Ethan Fetaya
ArXivPDFHTML

Papers citing "Learning the Pareto Front with Hypernetworks"

31 / 31 papers shown
Title
Reasoning BO: Enhancing Bayesian Optimization with Long-Context Reasoning Power of LLMs
Reasoning BO: Enhancing Bayesian Optimization with Long-Context Reasoning Power of LLMs
Zhuo Yang
Lingli Ge
Dong Han
Tianfan Fu
Yuqiang Li
32
0
0
19 May 2025
Joint Explainability-Performance Optimization With Surrogate Models for AI-Driven Edge Services
Foivos Charalampakos
Thomas Tsouparopoulos
Iordanis Koutsopoulos
57
1
0
10 Mar 2025
Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond
Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond
Weiyu Chen
Xiaoyuan Zhang
Baijiong Lin
Xi Lin
Han Zhao
Qingfu Zhang
James T. Kwok
84
4
0
19 Jan 2025
A Survey of Controllable Learning: Methods and Applications in Information Retrieval
A Survey of Controllable Learning: Methods and Applications in Information Retrieval
Chenglei Shen
Xiao Zhang
Teng Shi
Changshuo Zhang
Guofu Xie
Jun Xu
76
5
0
03 Jan 2025
Improving Pareto Set Learning for Expensive Multi-objective Optimization via Stein Variational Hypernetworks
Improving Pareto Set Learning for Expensive Multi-objective Optimization via Stein Variational Hypernetworks
Minh-Duc Nguyen
Phuong Mai Dinh
Quang-Huy Nguyen
L. P. Hoang
Dung D. Le
54
1
0
23 Dec 2024
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning
Mengmeng Chen
Xiaohu Wu
Xiaoli Tang
Tiantian He
Yew-Soon Ong
Qiqi Liu
Qicheng Lao
Han Yu
FedML
39
3
0
25 Oct 2024
Benchmarking Data Heterogeneity Evaluation Approaches for Personalized
  Federated Learning
Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning
Zhilong Li
Xiaohu Wu
Xiaoli Tang
Tiantian He
Yew-Soon Ong
Mengmeng Chen
Qiqi Liu
Qicheng Lao
Han Yu
FedML
47
1
0
09 Oct 2024
Pareto Front Approximation for Multi-Objective Session-Based Recommender Systems
Pareto Front Approximation for Multi-Objective Session-Based Recommender Systems
Timo Wilm
Philipp Normann
Felix Stepprath
34
2
0
23 Jul 2024
Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences
Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences
Nikolaos Dimitriadis
Pascal Frossard
François Fleuret
MoE
72
6
0
10 Jul 2024
Enhancing Domain Adaptation through Prompt Gradient Alignment
Enhancing Domain Adaptation through Prompt Gradient Alignment
Hoang Phan
Lam C. Tran
Quyen Tran
Trung Le
52
0
0
13 Jun 2024
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
Lu Li
Tianze Zhang
Zhiqi Bu
Suyuchen Wang
Huan He
Jie Fu
Yonghui Wu
Jiang Bian
Yong Chen
Yoshua Bengio
FedML
MoMe
102
3
0
11 Jun 2024
Preparing for Black Swans: The Antifragility Imperative for Machine
  Learning
Preparing for Black Swans: The Antifragility Imperative for Machine Learning
Ming Jin
45
2
0
18 May 2024
Evolutionary Preference Sampling for Pareto Set Learning
Evolutionary Preference Sampling for Pareto Set Learning
Rongguang Ye
Longcan Chen
Jinyuan Zhang
H. Ishibuchi
38
3
0
12 Apr 2024
Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems
Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems
Chikai Shang
Rongguang Ye
Jiaqi Jiang
Fangqing Gu
37
1
0
01 Apr 2024
Multi-objective Differentiable Neural Architecture Search
Multi-objective Differentiable Neural Architecture Search
R. Sukthanker
Arber Zela
B. Staffler
Samuel Dooley
Josif Grabocka
Frank Hutter
55
1
0
28 Feb 2024
A Hyper-Transformer model for Controllable Pareto Front Learning with
  Split Feasibility Constraints
A Hyper-Transformer model for Controllable Pareto Front Learning with Split Feasibility Constraints
Tran Anh Tuan
Nguyen Viet Dung
Tran Ngoc Thang
39
3
0
04 Feb 2024
Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
Yinuo Ren
Tesi Xiao
Tanmay Gangwani
A. Rangi
Holakou Rahmanian
Lexing Ying
Subhajit Sanyal
32
2
0
22 Nov 2023
Bi-level Multi-objective Evolutionary Learning: A Case Study on
  Multi-task Graph Neural Topology Search
Bi-level Multi-objective Evolutionary Learning: A Case Study on Multi-task Graph Neural Topology Search
Chao Wang
Licheng Jiao
Jiaxuan Zhao
Lingling Li
Xu Liu
F. Liu
Shuyuan Yang
39
5
0
06 Feb 2023
Improving Pareto Front Learning via Multi-Sample Hypernetworks
Improving Pareto Front Learning via Multi-Sample Hypernetworks
L. P. Hoang
Dung D. Le
Tuan A. Tran
Thang Tran Ngoc
24
24
0
02 Dec 2022
HMOE: Hypernetwork-based Mixture of Experts for Domain Generalization
HMOE: Hypernetwork-based Mixture of Experts for Domain Generalization
Jingang Qu
T. Faney
Zehao Wang
Patrick Gallinari
Soleiman Yousef
J. D. Hemptinne
OOD
29
7
0
15 Nov 2022
Pareto Manifold Learning: Tackling multiple tasks via ensembles of
  single-task models
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
Nikolaos Dimitriadis
P. Frossard
Franccois Fleuret
36
25
0
18 Oct 2022
Pareto Set Learning for Expensive Multi-Objective Optimization
Pareto Set Learning for Expensive Multi-Objective Optimization
Xi Lin
Zhiyuan Yang
Xiao-Yan Zhang
Qingfu Zhang
46
54
0
16 Oct 2022
Pareto Frontier Approximation Network (PA-Net) to Solve Bi-objective TSP
Pareto Frontier Approximation Network (PA-Net) to Solve Bi-objective TSP
Ishaan Mehta
Sharareh Taghipour
Sajad Saeedi
30
4
0
02 Mar 2022
Learning Proximal Operators to Discover Multiple Optima
Learning Proximal Operators to Discover Multiple Optima
Lingxiao Li
Noam Aigerman
Vladimir G. Kim
Jiajin Li
Kristjan Greenewald
Mikhail Yurochkin
Justin Solomon
47
1
0
28 Jan 2022
Pareto Domain Adaptation
Pareto Domain Adaptation
Fangrui Lv
Jian Liang
Kaixiong Gong
Shuang Li
Chi Harold Liu
Han Li
Di Liu
Guoren Wang
15
31
0
08 Dec 2021
Scalable Unidirectional Pareto Optimality for Multi-Task Learning with
  Constraints
Scalable Unidirectional Pareto Optimality for Multi-Task Learning with Constraints
Soumyajit Gupta
Gurpreet Singh
Raghu Bollapragada
Matthew Lease
30
4
0
28 Oct 2021
Scalable Pareto Front Approximation for Deep Multi-Objective Learning
Scalable Pareto Front Approximation for Deep Multi-Objective Learning
Michael Ruchte
Josif Grabocka
32
58
0
24 Mar 2021
Personalized Federated Learning using Hypernetworks
Personalized Federated Learning using Hypernetworks
Aviv Shamsian
Aviv Navon
Ethan Fetaya
Gal Chechik
FedML
41
327
0
08 Mar 2021
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic
  Multi-Objective Approach
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic Multi-Objective Approach
Suyun Liu
Luis Nunes Vicente
FaML
29
68
0
03 Aug 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
349
4,237
0
23 Aug 2019
ENet: A Deep Neural Network Architecture for Real-Time Semantic
  Segmentation
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Adam Paszke
Abhishek Chaurasia
Sangpil Kim
Eugenio Culurciello
SSeg
235
2,059
0
07 Jun 2016
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