Search Results for author: Zihao Chen

Found 19 papers, 3 papers with code

Isometric Immersion Learning with Riemannian Geometry

no code implementations23 Sep 2024 Zihao Chen, Wenyong Wang, Yu Xiang

Manifold learning has been proven to be an effective method for capturing the implicitly intrinsic structure of non-Euclidean data, in which one of the primary challenges is how to maintain the distortion-free (isometry) of the data representations.

Symbol-Level Precoding-Based Self-Interference Cancellation for ISAC Systems

no code implementations13 Sep 2024 Shu Cai, Zihao Chen, Ya-Feng Liu, Jun Zhang

Consider an integrated sensing and communication (ISAC) system where a base station (BS) employs a full-duplex radio to simultaneously serve multiple users and detect a target.

Bailing-TTS: Chinese Dialectal Speech Synthesis Towards Human-like Spontaneous Representation

no code implementations1 Aug 2024 Xinhan Di, Zihao Chen, Yunming Liang, Junjie Zheng, Yihua Wang, Chaofan Ding

Large-scale text-to-speech (TTS) models have made significant progress recently. However, they still fall short in the generation of Chinese dialectal speech.

Representation Learning Speech Synthesis +1

ON-OFF Neuromorphic ISING Machines using Fowler-Nordheim Annealers

no code implementations7 Jun 2024 Zihao Chen, Zhili Xiao, Mahmoud Akl, Johannes Leugring, Omowuyi Olajide, Adil Malik, Nik Dennler, Chad Harper, Subhankar Bose, Hector A. Gonzalez, Jason Eshraghian, Riccardo Pignari, Gianvito Urgese, Andreas G. Andreou, Sadasivan Shankar, Christian Mayr, Gert Cauwenberghs, Shantanu Chakrabartty

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using an annealing process that is governed by the physics of quantum mechanical tunneling using Fowler-Nordheim (FN).

Combinatorial Optimization

Energy-efficiency Limits on Training AI Systems using Learning-in-Memory

no code implementations21 Feb 2024 Zihao Chen, Johannes Leugering, Gert Cauwenberghs, Shantanu Chakrabartty

In this paper, we derive new theoretical lower bounds on energy dissipation when training AI systems using different LIM approaches.

Statistical Barriers to Affine-equivariant Estimation

no code implementations16 Oct 2023 Zihao Chen, Yeshwanth Cherapanamjeri

We investigate the quantitative performance of affine-equivariant estimators for robust mean estimation.

Energy landscape reveals the underlying mechanism of cancer-adipose conversion with gene network models

no code implementations22 May 2023 Zihao Chen, Jia Lu, Xing-Ming Zhao, Haiyang Yu, Chunhe Li

Our results revealed the underlying mechanism for intermediate cell states governing the CAC, and identified new potential drug combinations to induce cancer adipogenesis.

An Interpretable Loan Credit Evaluation Method Based on Rule Representation Learner

no code implementations3 Apr 2023 Zihao Chen, Xiaomeng Wang, Yuanjiang Huang, Tao Jia

More importantly, our model is used to test the correctness of the explanations generated by the post-hoc method, the results show that the post-hoc method is not always reliable.

JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its Applications

1 code implementation19 Jan 2023 Zihao Chen, Hisashi Handa, Kimiaki Shirahama

To overcome this, we propose a novel Japanese sentence representation framework, JCSE (derived from ``Contrastive learning of Sentence Embeddings for Japanese''), that creates training data by generating sentences and synthesizing them with sentences available in a target domain.

Contrastive Learning Domain Adaptation +7

Break The Spell Of Total Correlation In betaTCVAE

no code implementations17 Oct 2022 Zihao Chen, Wenyong Wang, Sai Zou

The novel model enables VAE to adjust the parameter capacity to divide dependent and independent data features flexibly.

Disentanglement

Magnitude-image based data-consistent deep learning method for MRI super resolution

no code implementations7 Sep 2022 Ziyan Lin, Zihao Chen

Magnetic Resonance Imaging (MRI) is important in clinic to produce high resolution images for diagnosis, but its acquisition time is long for high resolution images.

Deep Learning SSIM +1

Data-Consistent Non-Cartesian Deep Subspace Learning for Efficient Dynamic MR Image Reconstruction

no code implementations3 May 2022 Zihao Chen, Yuhua Chen, Yibin Xie, Debiao Li, Anthony G. Christodoulou

Non-Cartesian sampling with subspace-constrained image reconstruction is a popular approach to dynamic MRI, but slow iterative reconstruction limits its clinical application.

Image Reconstruction

Accelerating Training using Tensor Decomposition

1 code implementation10 Sep 2019 Mostafa Elhoushi, Ye Henry Tian, Zihao Chen, Farhan Shafiq, Joey Yiwei Li

In our approach, we train the model from scratch (i. e., randomly initialized weights) with its original architecture for a small number of epochs, then the model is decomposed, and then continue training the decomposed model till the end.

Tensor Decomposition

DeepShift: Towards Multiplication-Less Neural Networks

1 code implementation30 May 2019 Mostafa Elhoushi, Zihao Chen, Farhan Shafiq, Ye Henry Tian, Joey Yiwei Li

This family of neural network architectures (that use convolutional shifts and fully connected shifts) is referred to as DeepShift models.

Edge-computing Quantization

Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features

no code implementations2 Dec 2016 Zihao Chen, Luo Luo, Zhihua Zhang

Recently, there has been an increasing interest in designing distributed convex optimization algorithms under the setting where the data matrix is partitioned on features.

A Proximal Stochastic Quasi-Newton Algorithm

no code implementations31 Jan 2016 Luo Luo, Zihao Chen, Zhihua Zhang, Wu-Jun Li

It incorporates the Hessian in the smooth part of the function and exploits multistage scheme to reduce the variance of the stochastic gradient.

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