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Quantum Laplacian Eigenmap [article]

Yiming Huang, Xiaoyu Li
2016 arXiv   pre-print
Classical Laplacian eigenmap algorithm Laplacian eigenmap algorithm assumes that the data lies on or around a low-dimensional manifold in a high-dimensional space [5] , it builds a graph =( , ) G V E  ... 
arXiv:1611.00760v1 fatcat:ee5au4i5ebevffoqzwwkgev5pa

Therapy of cervical cancer using 131I-labeled nanoparticles

Wei Li, Danyang Sun, Ning Li, Yiming Shen, Yiming Hu, Jian Tan
2018 Journal of International Medical Research  
ORCID iD Wei Li http://orcid.org/0000-0002-2035-0134  ... 
doi:10.1177/0300060518761787 pmid:29658363 pmcid:PMC6023049 fatcat:z6ziajxr45bx5cjwizx42jtfei

Chargino and Neutralino Masses at ILC [article]

Yiming Li, Andrei Nomerotski
2010 arXiv   pre-print
The chargino/neutralino pair production is one of the benchmarking processes of ILC. These processes are interesting not only because it allows high precision measurement of chargino and neutralino masses, but also for the reason that the separation of W and Z bosons through their hadronic decay products requires excellent jet resolution being a good benchmark of the detector performance. The analysis based on the SiD detector concept with four jets and missing energy final state will be
more » ... ed. The uncertainty of chargino and neutralino cross sections can be determined with precision of 0.9% and 4.2% respectively. The mass uncertainties are obtained with a template fitting method achieving precision of better than 1 GeV.
arXiv:1007.0698v1 fatcat:frw6b5qbybbz7amgljvscvk7tm

An Integrated Framework for Two-pass Personalized Voice Trigger [article]

Dexin Liao, Jing Li, Yiming Zhi, Song Li, Qingyang Hong, Lin Li
2021 arXiv   pre-print
In this paper, we present the XMUSPEECH system for Task 1 of 2020 Personalized Voice Trigger Challenge (PVTC2020). Task 1 is a joint wake-up word detection with speaker verification on close talking data. The whole system consists of a keyword spotting (KWS) sub-system and a speaker verification (SV) sub-system. For the KWS system, we applied a Temporal Depthwise Separable Convolution Residual Network (TDSC-ResNet) to improve the system's performance. For the SV system, we proposed a multi-task
more » ... learning network, where phonetic branch is trained with the character label of the utterance, and speaker branch is trained with the label of the speaker. Phonetic branch is optimized with connectionist temporal classification (CTC) loss, which is treated as an auxiliary module for speaker branch. Experiments show that our system gets significant improvements compared with baseline system.
arXiv:2106.15950v1 fatcat:lddjye4qf5gylnw7tvjr7534rq

Oriental Language Recognition (OLR) 2020: Summary and Analysis [article]

Jing Li, Binling Wang, Yiming Zhi, Zheng Li, Lin Li, Qingyang Hong, Dong Wang
2021 arXiv   pre-print
Acknowledgements We would like to thank Ming Li at Duke Kunshan University, Xiaolei Zhang at Northwestern Polytechnical University for their help in organizing this OLR 2020 challenge.  ... 
arXiv:2107.05365v1 fatcat:iotl7l7qrvhdzpoexdc6iugaym

Online Active Regression [article]

Cheng Chen, Yi Li, Yiming Sun
2022 arXiv   pre-print
Active regression considers a linear regression problem where the learner receives a large number of data points but can only observe a small number of labels. Since online algorithms can deal with incremental training data and take advantage of low computational cost, we consider an online extension of the active regression problem: the learner receives data points one by one and immediately decides whether it should collect the corresponding labels. The goal is to efficiently maintain the
more » ... ession of received data points with a small budget of label queries. We propose novel algorithms for this problem under ℓ_p loss where p∈[1,2]. To achieve a (1+ϵ)-approximate solution, our proposed algorithms only require 𝒪̃(ϵ^-1 d log(nκ)) queries of labels, where n is the number of data points and κ is a quantity, called the condition number, of the data points. The numerical results verify our theoretical results and show that our methods have comparable performance with offline active regression algorithms.
arXiv:2207.05945v2 fatcat:wlu3uottjbflldcvdi43gt6yjy

Retrospective study

Chao Lu, Xueyou Lv, Yiming Lin, Dejian Li, Lihua Chen, Feng Ji, Youming Li, Chaohui Yu
2016 Medicine  
Conventional forceps biopsy (CFB) is the most popular way to screen for gastric epithelial neoplasia (GEN) and adenocarcinoma of gastric epithelium. The aim of this study was to compare the diagnostic accuracy between conventional forceps biopsy and endoscopic submucosal dissection (ESD). Four hundred forty-four patients who finally undertook ESD in our hospital were enrolled from Jan 1, 2009 to Sep 1, 2015. We retrospectively assessed the characteristics of pathological results of CFB and ESD.
more » ... The concordance rate between CFB and ESD specimens was 68.92% (306/444). Men showed a lower concordance rate (63.61% vs 79.33%; P = 0.001) and concordance patients were younger (P = 0.048). In multivariate analysis, men significantly had a lower concordance rate (coefficient À0.730, P = 0.002) and a higher rate of pathological upgrade (coefficient À0.648, P = 0.015). Locations of CFB did not influence the concordance rate statistically. The concordance rate was relatively high in our hospital. According to our analysis, old men plus gastric fundus or antrum of CFB were strongly suggested to perform ESD if precancerous lesions were found. And young women with low-grade intraepithelial neoplasia could select regular follow-up. Abbreviations: CFB = conventional forceps biopsy, CIC = chronic inflammation change, ESD = endoscopic submucosal dissection, GEN = gastric epithelial neoplasia, GIST = gastrointestinal stromal tumors, HGIN = high-grade intraepithelial neoplasia/ dysplasia, LGIN = low-grade intraepithelial neoplasia/dysplasia.
doi:10.1097/md.0000000000004353 pmid:27472723 pmcid:PMC5265860 fatcat:43766ntg4ncvpjqwb4digdeylu

Single-pixel coherent diffraction imaging [article]

Meng Li, Liheng Bian, Guoan Zheng, Andrew Maiden, Yang Liu, Yiming Li, Qionghai Dai, Jun Zhang
2020 arXiv   pre-print
Complex-field imaging is indispensable for numerous applications at wavelengths from X-ray to THz, with amplitude describing transmittance (or reflectivity) and phase revealing intrinsic structure of the target object. Coherent diffraction imaging (CDI) employs iterative phase retrieval algorithms to process diffraction measurements and is the predominant non-interferometric method to image complex fields. However, the working spectrum of CDI is quite narrow, because the diffraction
more » ... on which it relies require dense array detection with ultra-high dynamic range. Here we report a single-pixel CDI technique that works for a wide waveband. A single-pixel detector instead of an array sensor is employed in the far field for detection. It repeatedly records the DC-only component of the diffracted wavefront scattered from an object as it is illuminated by a sequence of binary modulation patterns. This decreases the measurements' dynamic range by several orders of magnitude. We employ an efficient single-pixel phase-retrieval algorithm to jointly recover the object's 2D amplitude and phase maps from the 1D intensity-only measurements. No a priori object information is needed in the recovery process. We validate the technique's quantitative phase imaging nature using both calibrated phase objects and biological samples, and demonstrate its wide working spectrum with both 488-nm visible light and 980-nm near-infrared light. Our approach paves the way for complex-field imaging in a wider waveband where 2D detector arrays are not available, with broad applications in life and material sciences.
arXiv:2003.14237v1 fatcat:ogw3tyeytjbdfdledsxqq3lcdu

Implicit Kernel Learning [article]

Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos
2019 arXiv   pre-print
Different probability metrics have been studied (Goodfellow et al., 2014; Li et al., 2015; Dziugaite et al., 2015; Nowozin et al., 2016; Li et al., 2017; Gulrajani et al., 2017; Mroueh et al., 2018; Arbel  ...  Li et al. (2017) propose MMD GAN, which trains g θ via min θ max k∈K M k (P X , P θ ), where K is a pre-defined set of kernels.  ... 
arXiv:1902.10214v1 fatcat:4gpv6ml2wzelrfomlqfeacy2hy

Kernel Stein Generative Modeling [article]

Wei-Cheng Chang, Chun-Liang Li, Youssef Mroueh, Yiming Yang
2020 arXiv   pre-print
We are interested in gradient-based Explicit Generative Modeling where samples can be derived from iterative gradient updates based on an estimate of the score function of the data distribution. Recent advances in Stochastic Gradient Langevin Dynamics (SGLD) demonstrates impressive results with energy-based models on high-dimensional and complex data distributions. Stein Variational Gradient Descent (SVGD) is a deterministic sampling algorithm that iteratively transports a set of particles to
more » ... proximate a given distribution, based on functional gradient descent that decreases the KL divergence. SVGD has promising results on several Bayesian inference applications. However, applying SVGD on high dimensional problems is still under-explored. The goal of this work is to study high dimensional inference with SVGD. We first identify key challenges in practical kernel SVGD inference in high-dimension. We propose noise conditional kernel SVGD (NCK-SVGD), that works in tandem with the recently introduced Noise Conditional Score Network estimator. NCK is crucial for successful inference with SVGD in high dimension, as it adapts the kernel to the noise level of the score estimate. As we anneal the noise, NCK-SVGD targets the real data distribution. We then extend the annealed SVGD with an entropic regularization. We show that this offers a flexible control between sample quality and diversity, and verify it empirically by precision and recall evaluations. The NCK-SVGD produces samples comparable to GANs and annealed SGLD on computer vision benchmarks, including MNIST and CIFAR-10.
arXiv:2007.03074v1 fatcat:y4rt6l2vevexvc3mkhnefck2zu

Training-Set Distillation for Real-Time UAV Object Tracking [article]

Fan Li, Changhong Fu, Fuling Lin, Yiming Li, Peng Lu
2020 arXiv   pre-print
Correlation filter (CF) has recently exhibited promising performance in visual object tracking for unmanned aerial vehicle (UAV). Such online learning method heavily depends on the quality of the training-set, yet complicated aerial scenarios like occlusion or out of view can reduce its reliability. In this work, a novel time slot-based distillation approach is proposed to efficiently and effectively optimize the training-set's quality on the fly. A cooperative energy minimization function is
more » ... tablished to score the historical samples adaptively. To accelerate the scoring process, frames with high confident tracking results are employed as the keyframes to divide the tracking process into multiple time slots. After the establishment of a new slot, the weighted fusion of the previous samples generates one key-sample, in order to reduce the number of samples to be scored. Besides, when the current time slot exceeds the maximum frame number, which can be scored, the sample with the lowest score will be discarded. Consequently, the training-set can be efficiently and reliably distilled. Comprehensive tests on two well-known UAV benchmarks prove the effectiveness of our method with real-time speed on a single CPU.
arXiv:2003.05326v1 fatcat:46tu53hkmna7jmhiprnqzryw54

Heavy flavour spectroscopy at LHC [article]

Yiming Li
2014 arXiv   pre-print
The pp collision data collected in the LHC Run I provides a great opportunity for heavy flavour studies. The latest results on exotic states, heavy baryon and B_c^+ mesons are reviewed.
arXiv:1409.4020v2 fatcat:iftpkdp5tna6lkbtcsfahc5g24

Predictive Visual Tracking: A New Benchmark and Baseline Approach [article]

Bowen Li, Yiming Li, Junjie Ye, Changhong Fu, Hang Zhao
2021 arXiv   pre-print
* Equal contribution. u Corresponding author. 1 Bowen Li, Junjie Ye, and Changhong Fu are with School of Mechanical Engineering, Tongji University, Shanghai, China changhongfu@tongji.edu.cn Yiming Li  ... 
arXiv:2103.04508v1 fatcat:d4or4q3e5zairgf7ziwmzmwj7y

OLR 2021 Challenge: Datasets, Rules and Baselines [article]

Binling Wang, Wenxuan Hu, Jing Li, Yiming Zhi, Zheng Li, Qingyang Hong, Lin Li, Dong Wang, Liming Song, Cheng Yang
2021 arXiv   pre-print
This paper introduces the sixth Oriental Language Recognition (OLR) 2021 Challenge, which intends to improve the performance of language recognition systems and speech recognition systems within multilingual scenarios. The data profile, four tasks, two baselines, and the evaluation principles are introduced in this paper. In addition to the Language Identification (LID) tasks, multilingual Automatic Speech Recognition (ASR) tasks are introduced to OLR 2021 Challenge for the first time. The
more » ... enge this year focuses on more practical and challenging problems, with four tasks: (1) constrained LID, (2) unconstrained LID, (3) constrained multilingual ASR, (4) unconstrained multilingual ASR. Baselines for LID tasks and multilingual ASR tasks are provided, respectively. The LID baseline system is an extended TDNN x-vector model constructed with Pytorch. A transformer-based end-to-end model is provided as the multilingual ASR baseline system. These recipes will be online published, and available for participants to construct their own LID or ASR systems. The baseline results demonstrate that those tasks are rather challenging and deserve more effort to achieve better performance.
arXiv:2107.11113v1 fatcat:badzpctmandrtf2xx5darqedp4

Interlocked multi-armed carbon for stable oxygen reduction

Yiming Li, Lei Li, Longfeng Zhu, Li Gu, Xuebo Cao
2016 Chemical Communications  
N-Doped multi-armed carbon with an interlocked structure shows high oxygen reduction activity and resistance to methanol crossover effects.
doi:10.1039/c6cc01095d pmid:26960995 fatcat:oxfsowdbqneynjorr3acsqojly
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