Publications (41)
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
Malte J. Rasch, Charles Mackin, Manuel Le Gallo +10
Analog in-memory computing (AIMC) -- a promising approach for energy-efficient acceleration of deep learning workloads -- computes matrix-vector multiplications (MVMs) but only app…
Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs
Jung Hyun Lee, Seungjae Shin, Vinnam Kim +2
As the rapid scaling of large language models (LLMs) poses significant challenges for deployment on resource-constrained devices, there is growing interest in extremely low-bit qua…
Visual Path Tracking Control for Park Scene
Linjiong Zhu, Wenfu Wang, Weijie Yang +2
Autonomous driving application is developing towards specific scenes. Park scene has features such as low speed, fixed routes, short connection, less complex traffic, and hence is…
Analog Foundation Models
Julian Büchel, Iason Chalas, Giovanni Acampa +7
Analog in-memory computing (AIMC) is a promising compute paradigm to improve speed and power efficiency of neural network inference beyond the limits of conventional von Neumann-ba…
Enhancing Gaussian Estimation of Distribution Algorithm by Exploiting Evolution Direction with Archive
Yongsheng Liang, Zhigang Ren, Xianghua Yao +2
As a typical model-based evolutionary algorithm (EA), estimation of distribution algorithm (EDA) possesses unique characteristics and has been widely applied to global optimization…
A Scoring Method for Driving Safety Credit Using Trajectory Data
Wenfu Wang, Weijie Yang, An Chen +1
Urban traffic systems worldwide are suffering from severe traffic safety problems. Traffic safety is affected by many complex factors, and heavily related to all drivers' behaviors…
Nonconcave Portfolio Choice under Smooth Ambiguity
Emanuele Borgonovo, An Chen, Massimo Marinacci +1
We study continuous-time portfolio choice with nonlinear payoffs under smooth ambiguity and Bayesian learning. We develop a general framework for dynamic, non-concave asset allocat…
Sparsity-Based Channel Estimation Exploiting Deep Unrolling for Downlink Massive MIMO
An Chen, Wenbo Xu, Liyang Lu +1
Massive multiple-input multiple-output (MIMO) enjoys great advantage in 5G wireless communication systems owing to its spectrum and energy efficiency. However, hundreds of antennas…
Rectify Then Diffuse: Disentangling Concepts Before Denoising Trajectory Unfolds
Ning Zhu, An Chen, Mengfei Zhao +4
Text-to-image diffusion models can generate individual concepts well, but they often omit or merge concepts incorrectly with multiple concepts. We trace these failures to an early…
Optimal investment with time-varying stochastic endowments
Christoph Belak, An Chen, Carla Mereu +1
This paper considers a utility maximization and optimal asset allocation problem in the presence of a stochastic endowment that cannot be fully hedged through trading in the financ…
Downlink Massive MIMO Channel Estimation via Deep Unrolling : Sparsity Exploitations in Angular Domain
An Chen, Wenbo Xu, Liyang Lu +1
In frequency division duplex (FDD) massive MIMO systems, reliable downlink channel estimation is essential for the subsequent data transmission but is realized at the cost of massi…
Observation of Coherent Perfect Acoustic Absorption at an Exceptional Point
Yi-Fei Xia, Zi-Xiang Xu, Yu-Ting Yan +5
Non-Hermitian systems have recently shown new possibilities to manipulate wave scattering by exploiting loss, yet coherent perfect absorption at an exceptional point (CPA EP) remai…
A Surrogate-Assisted Variable Grouping Algorithm for General Large Scale Global Optimization Problems
An Chen, Zhigang Ren, Muyi Wang +3
Problem decomposition plays a vital role when applying cooperative coevolution (CC) to large scale global optimization problems. However, most learning-based decomposition algorith…
Niching an Archive-based Gaussian Estimation of Distribution Algorithm via Adaptive Clustering
Yongsheng Liang, Zhigang Ren, Bei Pang +1
As a model-based evolutionary algorithm, estimation of distribution algorithm (EDA) possesses unique characteristics and has been widely applied to global optimization. However, tr…
On the equivalence between Value-at-Risk- and Expected Shortfall-based risk measures in non-concave optimization
An Chen, Mitja Stadje, Fangyuan Zhang
We study a non-concave optimization problem in which a financial company maximizes the expected utility of the surplus under a risk-based regulatory constraint. For this problem, w…
One Knob to Rule Them All: A Unified Optimal Transport View of Cold-Start Active Learning
Ning Zhu, Xiaochuan Ma, Juntao Xu +4
Cold-Start Active Learning (CSAL) aims to select a valuable subset from an unlabeled pool without any prior knowledge or human assistance. Existing methods take diverse routes base…
FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning
Phung Lai, Xiaopeng Jiang, Hai Phan +5
Federated Learning (FL) allows collaborative training among multiple devices without data sharing, thus enabling privacy-sensitive applications on mobile or Internet of Things (IoT…
Enhancing hierarchical surrogate-assisted evolutionary algorithm for high-dimensional expensive optimization via random projection
Xiaodong Ren, Daofu Guo, Zhigang Ren +2
By remarkably reducing real fitness evaluations, surrogate-assisted evolutionary algorithms (SAEAs), especially hierarchical SAEAs, have been shown to be effective in solving compu…
Laypunov Irregular Points With Distributional Chaos
An Chen, Xueting Tian
It follows from Oseledec Multiplicative Ergodic Theorem (or Kingmans Subadditional Ergodic Theorem) that the Lyapunov-irregular set of points for which the Oseledec averages of a g…
A Fast Differential Grouping Algorithm for Large Scale Black-Box Optimization
Zhigang Ren, An Chen, Yaochu Jin +3
Decomposition plays a significant role in cooperative co-evolution which shows great potential in large scale black-box optimization. However, current popular decomposition algorit…
Strongly distributional chaos in the sets of twelve different types of non-recurrent points
An Chen, Xiaobo Hou, Wanshan Lin +1
In present paper we mainly focus on non-recurrent dynamical orbits with empty syndetic center and show that twelve different statistical structures over mixing expanding maps or tr…
Intergenerational risk sharing in a Defined Contribution pension system: analysis with Bayesian optimization
An Chen, Motonobu Kanagawa, Fangyuan Zhang
We study a fully funded, collective defined-contribution (DC) pension system with multiple overlapping generations. We investigate whether the welfare of participants can be improv…
Surrogate Model Assisted Cooperative Coevolution for Large Scale Optimization
Zhigang Ren, Bei Pang, Yongsheng Liang +2
It has been shown that cooperative coevolution (CC) can effectively deal with large scale optimization problems (LSOPs) through a divide-and-conquer strategy. However, its performa…
Zone-based Federated Learning for Mobile Sensing Data
Xiaopeng Jiang, Thinh On, NhatHai Phan +5
Mobile apps, such as mHealth and wellness applications, can benefit from deep learning (DL) models trained with mobile sensing data collected by smart phones or wearable devices. H…
Distinguishing high-mass binary neutron stars from binary black holes with second- and third-generation gravitational wave observatories
An Chen, Nathan K. Johnson-McDaniel, Tim Dietrich +1
(Abridged) While the gravitational-wave (GW) signal GW170817 was accompanied by a variety of electromagnetic (EM) counterparts, sufficiently high-mass binary neutron star (BNS) mer…
A Global Information Based Adaptive Threshold for Grouping Large Scale Global Optimization Problems
An Chen, Yipeng Zhang, Zhigang Ren +2
By taking the idea of divide-and-conquer, cooperative coevolution (CC) provides a powerful architecture for large scale global optimization (LSGO) problems, but its efficiency reli…
Acoustic topological Jackiw-Rebbi states at symmetry broken interfaces
Yifei Xia, An Chen, Ting Zhang +4
Topological insulators, a fundamental concept in modern condensed matter physics, support localized states at the interfaces between insulators exhibiting different topological pha…
Birkhoff sum convergence of Fréchet observables to stable laws for Gibbs-Markov systems and applications
An Chen, Matthew Nicol, Andrew Török
We use a Poisson point process approach to prove distributional convergence to a stable law for non square-integrable observables , mostly of the form $Ï(x) = d(x,…
Optimal investment under partial information and robust VaR-type constraint
Nicole Bäuerle, An Chen
This paper extends the utility maximization literature by combining partial information and (robust) regulatory constraints. Partial information is characterized by the fact that t…
A Surrogate-Assisted Highly Cooperative Coevolutionary Algorithm for Hyperparameter Optimization in Deep Convolutional Neural Network
An Chen, Zhigang Ren, Muyi Wang +3
Convolutional neural networks (CNNs) have gained remarkable success in recent years. However, their performance highly relies on the architecture hyperparameters, and finding prope…
Distributional chaos in multifractal analysis, recurrence and transitivity
An Chen, Xueting Tian
There are lots of results to study dynamical complexity on irregular sets and level sets of ergodic average from the perspective of density in base space, Hausdorff dimension, Lebe…
Sufficient Conditions for Unique Optimizer of Two-Dimensional Atomic Norm Minimization Under Multiple Frequencies
An Chen, Wenbo Xu
Atomic norm minimization (ANM) has been extensively applied for gridless angle estimation. However, with the increase of the number of antennas and the communication frequencies in…
Striking the Balance: Life Insurance Timing and Asset Allocation in Financial Planning
An Chen, Giorgio Ferrari, Shihao Zhu
This paper investigates the consumption and investment decisions of an individual facing uncertain lifespan and stochastic labor income within a Black-Scholes market framework. A k…
On the Investment Strategies in Occupational Pension Plans
Frank Bosserhoff, An Chen, Nils Sorensen +1
Demographic changes increase the necessity to base the pension system more and more on the second and the third pillar, namely the occupational and private pension plans; this pape…
Molecular HDD Logic for Encrypted Massive Data Storage
Bingjie Guo, Xinhui Chen, An Chen +11
Organic memories, with small dimension, fast speed and long retention features, are considered as promising candidates for massive data archiving. In order to satisfy the re-quirem…
Experimental Realization of Weyl Exceptional Rings in a Synthetic Three-Dimensional Non-Hermitian Phononic Crystal
Zheng-wei Li, Jing-jing Liu, Ze-Guo Chen +5
Weyl points (WPs) are isolated degeneracies carrying quantized topological charges, and are therefore robust against Hermitian perturbations. WPs are predicted to spread to the Wey…
FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps
Xiaopeng Jiang, Han Hu, Vijaya Datta Mayyuri +6
This article presents the design, implementation, and evaluation of FLSys, a mobile-cloud federated learning (FL) system, which can be a key component for an open ecosystem of FL m…
Knowledge-Reuse Transfer Learning Methods in Molecular and Material Science
An Chen, Zhilong Wang, Karl Luigi Loza Vidaurre +6
Molecules and materials are the foundation for the development of modern advanced industries such as energy storage systems and semiconductor devices. However, traditional trial-an…
AlphaMat: A Material Informatics Hub Connecting Data, Features, Models and Applications
Zhilong Wang, Junfei Cai, An Chen +6
The development of modern civil industry, energy and information technology is inseparable from the rapid explorations of new materials, which are hampered by months to years of pa…
An Eigenspace Divide-and-Conquer Approach for Large-Scale Optimization
Zhigang Ren, Yongsheng Liang, Muyi Wang +2
Divide-and-conquer-based (DC-based) evolutionary algorithms (EAs) have achieved notable success in dealing with large-scale optimization problems (LSOPs). However, the appealing pe…
Enhancing Cooperative Coevolution for Large Scale Optimization by Adaptively Constructing Surrogate Models
Bei Pang, Zhigang Ren, Yongsheng Liang +1
It has been shown that cooperative coevolution (CC) can effectively deal with large scale optimization problems (LSOPs) through a divide-and-conquer strategy. However, its performa…