no code implementations • EMNLP 2021 • Sixuan Wu, Jian Li, Peng Zhang, Yue Zhang
Recent research has investigated quantum NLP, designing algorithms that process natural language in quantum computers, and also quantum-inspired algorithms that improve NLP performance on classical computers.
no code implementations • Findings (ACL) 2022 • Jian Li, Jieming Zhu, Qiwei Bi, Guohao Cai, Lifeng Shang, Zhenhua Dong, Xin Jiang, Qun Liu
Accurately matching user’s interests and candidate news is the key to news recommendation.
no code implementations • Findings (ACL) 2022 • Xianghong Fang, Jian Li, Lifeng Shang, Xin Jiang, Qun Liu, Dit-yan Yeung
While variational autoencoders (VAEs) have been widely applied in text generation tasks, they are troubled by two challenges: insufficient representation capacity and poor controllability.
no code implementations • Findings (ACL) 2022 • Qiwei Bi, Jian Li, Lifeng Shang, Xin Jiang, Qun Liu, Hanfang Yang
With the adoption of large pre-trained models like BERT in news recommendation, the above way to incorporate multi-field information may encounter challenges: the shallow feature encoding to compress the category and entity information is not compatible with the deep BERT encoding.
1 code implementation • 1 May 2022 • Jian Li, Yong liu, Yingying Zhang
Recent theoretical studies illustrated that kernel ridgeless regression can guarantee good generalization ability without an explicit regularization.
no code implementations • 22 Apr 2022 • Yilin Kang, Yong liu, Jian Li, Weiping Wang
In this paper, by introducing Generalized Bernstein condition, we propose the first $\mathcal{O}\big(\frac{\sqrt{p}}{n\epsilon}\big)$ high probability excess population risk bound for differentially private algorithms under the assumptions $G$-Lipschitz, $L$-smooth, and Polyak-{\L}ojasiewicz condition, based on gradient perturbation method.
no code implementations • 11 Apr 2022 • Yilin Kang, Yong liu, Jian Li, Weiping Wang
To the best of our knowledge, this is the first time to analyze the generalization performance of general minimax paradigm, taking differential privacy into account.
no code implementations • 26 Feb 2022 • Guojun Xiong, Shufan Wang, Jian Li, Rahul Singh
In this paper, we consider the problem of content caching at the wireless edge with unreliable channels to minimize average content request latency.
no code implementations • 26 Jan 2022 • Jian Li, Bin Zhang, Yabiao Wang, Ying Tai, Zhenyu Zhang, Chengjie Wang, Jilin Li, Xiaoming Huang, Yili Xia
Along with current multi-scale based detectors, Feature Aggregation and Enhancement (FAE) modules have shown superior performance gains for cutting-edge object detection.
no code implementations • 18 Jan 2022 • Xin Li, Jian Li, Zhihong Jeff Xia, Nikolaos Georgakarakos
Most recently, machine learning has been used to study the dynamics of integrable Hamiltonian systems and the chaotic 3-body problem.
no code implementations • 12 Jan 2022 • Jiangning Zhang, Chao Xu, Jian Li, Yue Han, Yabiao Wang, Ying Tai, Yong liu
In the practical application of restoring low-resolution gray-scale images, we generally need to run three separate processes of image colorization, super-resolution, and dows-sampling operation for the target device.
no code implementations • 15 Dec 2021 • Shuo Sun, Rundong Wang, Xu He, Junlei Zhu, Jian Li, Bo An
However, it is hard to apply existing RL methods to intraday trading due to the following three limitations: 1) overlooking micro-level market information (e. g., limit order book); 2) only focusing on local price fluctuation and failing to capture the overall trend of the whole trading day; 3) neglecting the impact of market risk.
1 code implementation • 25 Nov 2021 • Jin Xu, Mingjian Chen, Jianqiang Huang, Xingyuan Tang, Ke Hu, Jian Li, Jia Cheng, Jun Lei
Graph Neural Networks (GNNs) have become increasingly popular and achieved impressive results in many graph-based applications.
no code implementations • 8 Nov 2021 • Hang Qiu, Ioanna Vavelidou, Jian Li, Evgenya Pergament, Pete Warden, Sandeep Chinchali, Zain Asgar, Sachin Katti
The key challenge is that there is not much visibility into ML inference execution on edge devices, and very little awareness of potential issues during the edge deployment process.
1 code implementation • 19 Oct 2021 • Yuxi Li, Boshen Zhang, Jian Li, Yabiao Wang, Weiyao Lin, Chengjie Wang, Jilin Li, Feiyue Huang
We demonstrate that both temporal grains are beneficial to atomic action recognition.
1 code implementation • ACL 2022 • Yanan Zheng, Jing Zhou, Yujie Qian, Ming Ding, Chonghua Liao, Jian Li, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, Zhilin Yang
The few-shot natural language understanding (NLU) task has attracted much recent attention.
no code implementations • 20 Sep 2021 • Guojun Xiong, Jian Li, Rahul Singh
We call it the R(MA)^2B-UCB algorithm.
no code implementations • 12 Sep 2021 • Gang Yan, Hao Wang, Jian Li
In this work, we show that the final test accuracy of FL is dramatically affected by the early phase of the training process, i. e., FL exhibits critical learning periods, in which small gradient errors can have irrecoverable impact on the final test accuracy.
no code implementations • 31 Aug 2021 • Pengfei Zhu, Xiaoguang Li, Jian Li, Hai Zhao
Open-domain Question Answering (ODQA) has achieved significant results in terms of supervised learning manner.
Machine Reading Comprehension
Open-Domain Question Answering
no code implementations • 29 Aug 2021 • Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Jian Li
Weight sharing has become the \textit{de facto} approach to reduce the training cost of neural architecture search (NAS) by reusing the weights of shared operators from previously trained child models.
no code implementations • 28 Aug 2021 • Hanfei Yu, Hao Wang, Jian Li, Xu Yuan, Seung-Jong Park
Serverless computing automates fine-grained resource scaling and simplifies the development and deployment of online services with stateless functions.
1 code implementation • ACL 2022 • Jing Zhou, Yanan Zheng, Jie Tang, Jian Li, Zhilin Yang
Most previous methods for text data augmentation are limited to simple tasks and weak baselines.
no code implementations • 26 Jul 2021 • Liang Zeng, Lei Wang, Hui Niu, Jian Li, Ruchen Zhang, Zhonghao Dai, Dewei Zhu, Ling Wang
Price movement forecasting aims at predicting the future trends of financial assets based on the current market conditions and other relevant information.
1 code implementation • 16 Jun 2021 • Xianghong Fang, Haoli Bai, Jian Li, Zenglin Xu, Michael Lyu, Irwin King
We further design discrete latent space for the variational attention and mathematically show that our model is free from posterior collapse.
no code implementations • 12 Jun 2021 • Haike Xu, Jian Li
Our algorithm achieves an (approximation) regret bound of $\tilde{O}\left(d\sqrt{KT}\right)$.
no code implementations • 10 Jun 2021 • Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li
Extensive experiments on node classification, graph classification, and edge prediction demonstrate the effectiveness of AKE-GNN.
1 code implementation • NeurIPS 2021 • Jiangning Zhang, Chao Xu, Jian Li, Wenzhou Chen, Yabiao Wang, Ying Tai, Shuo Chen, Chengjie Wang, Feiyue Huang, Yong liu
Inspired by biological evolution, we explain the rationality of Vision Transformer by analogy with the proven practical Evolutionary Algorithm (EA) and derive that both of them have consistent mathematical representation.
no code implementations • 30 May 2021 • Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu
The technical challenge of NAS-BERT is that training a big supernet on the pre-training task is extremely costly.
no code implementations • 7 May 2021 • Yilin Kang, Yong liu, Jian Li, Weiping Wang
Pairwise learning focuses on learning tasks with pairwise loss functions, depends on pairs of training instances, and naturally fits for modeling relationships between pairs of samples.
no code implementations • 31 Mar 2021 • Xiaolei Shang, Jian Li, Petre Stoica
The recently proposed hyperparameter-free (and hence user friendly) weighted SPICE algorithms, including SPICE, LIKES, SLIM and IAA, achieve excellent parameter estimation performance for data sampled with high precision.
no code implementations • 21 Mar 2021 • Jiaying Ren, Tianyi Zhang, Jian Li, Petre Stoica
In a previous paper, a relaxation-based algorithm, referred to as 1bRELAX, has been proposed to iteratively maximize the likelihood function.
no code implementations • 19 Mar 2021 • Tianyi Zhang, Jiaying Ren, Jian Li, Lam H. Nguyen, Petre Stoica
Radio frequency interference (RFI) mitigation and radar echo recovery are critically important for the proper functioning of ultra-wideband (UWB) radar systems using one-bit sampling techniques.
no code implementations • 24 Feb 2021 • Kun Liu, Tongjun Liu, Wei Fang, Jian Li, Qin Wang
Quantum correlation is a fundamental property which distinguishes quantum systems from classical ones, and it is also a fragile resource under projective measurement.
Quantum Physics
no code implementations • ICLR 2021 • Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu
Recently, various auxiliary tasks have been proposed to accelerate representation learning and improve sample efficiency in deep reinforcement learning (RL).
no code implementations • 17 Feb 2021 • Tianyi Zhang, Jiaying Ren, Jian Li, Lam H. Nguyen, Petre Stoica
A one-bit UWB system obtains its signed measurements via a low-cost and high rate sampling scheme, referred to as the Continuous Time Binary Value (CTBV) technology.
no code implementations • 11 Feb 2021 • Guojun Xiong, Gang Yan, Rahul Singh, Jian Li
In this paradigm, each worker maintains a local estimate of the optimal parameter vector, and iteratively updates it by waiting and averaging all estimates obtained from its neighbors, and then corrects it on the basis of its local dataset.
no code implementations • 10 Feb 2021 • Jian Li, Ruo-Yu Liu, Emma de Ona Wilhelmi, Diego F. Torres, Qian-Cheng Liu, Matthew Kerr, Rolf Buehler, Yang Su, Hao-Ning He, Meng-Yuan Xiao
The unidentified TeV source MGRO J1908+06, with emission extending from hundreds of GeV to beyond 100TeV, is one of the most intriguing sources in the Galactic plane.
High Energy Astrophysical Phenomena
no code implementations • 28 Jan 2021 • Jian Li, Chockalingam Senthilnathan, Tal Cohen
The combination of fast propagation speeds and highly localized nature has hindered the direct observation of the evolution of shock waves at the molecular scale.
Soft Condensed Matter
no code implementations • 14 Jan 2021 • Jian Li, Raziel Alvarez
Integer quantization of neural networks can be defined as the approximation of the high precision computation of the canonical neural network formulation, using reduced integer precision.
no code implementations • 10 Jan 2021 • Guojun Xiong, Rahul Singh, Jian Li
We pose the problem as a Markov decision process (MDP) in which the system state is given by describing, for each service, the number of customers that are currently waiting at the edge to obtain the service.
no code implementations • 22 Nov 2020 • Bokai Zhang, Jian Li, Juan-mei Hu, Lei Liu
The dynamics of polymer-nanoparticle (NP) mixtures, which involves multiple scales and system-specific variables, has posed a long-standing challenge on its theoretical description.
Soft Condensed Matter
no code implementations • 10 Nov 2020 • Zhiguo Wang, Jiawei Zhang, Tsung-Hui Chang, Jian Li, Zhi-Quan Luo
While many distributed optimization algorithms have been proposed for solving smooth or convex problems over the networks, few of them can handle non-convex and non-smooth problems.
1 code implementation • 17 Oct 2020 • Robert David, Jared Duke, Advait Jain, Vijay Janapa Reddi, Nat Jeffries, Jian Li, Nick Kreeger, Ian Nappier, Meghna Natraj, Shlomi Regev, Rocky Rhodes, Tiezhen Wang, Pete Warden
We introduce TensorFlow Lite Micro (TF Micro), an open-source ML inference framework for running deep-learning models on embedded systems.
1 code implementation • 3 Oct 2020 • Chuheng Zhang, Yuanqi Li, Xi Chen, Yifei Jin, Pingzhong Tang, Jian Li
Modern machine learning models (such as deep neural networks and boosting decision tree models) have become increasingly popular in financial market prediction, due to their superior capacity to extract complex non-linear patterns.
no code implementations • NeurIPS 2020 • Hu Liu, Jing Lu, Xiwei Zhao, Sulong Xu, Hao Peng, Yutong Liu, Zehua Zhang, Jian Li, Junsheng Jin, Yongjun Bao, Weipeng Yan
First, conventional attentions mostly limit the attention field only to a single user's behaviors, which is not suitable in e-commerce where users often hunt for new demands that are irrelevant to any historical behaviors.
no code implementations • 28 Sep 2020 • Shaoming Song, Yunfeng Shao, Jian Li
This paper proposes Loosely Coupled Federated Learning (LC-FL), a framework using generative models as transmission media to achieve low communication cost and heterogeneous federated learning.
no code implementations • 9 Aug 2020 • Jian Li, Lan Zhang, Kaiping Xue, Yuguang Fang
Specifically, to guarantee the worst-case achievable secrecy rate among multiple legitimate users, we formulate a max-min problem that can be solved by an alternative optimization method to decouple it into multiple sub-problems.
no code implementations • 9 Aug 2020 • Jin Xu, Xu Tan, Yi Ren, Tao Qin, Jian Li, Sheng Zhao, Tie-Yan Liu
However, there are more than 6, 000 languages in the world and most languages are lack of speech training data, which poses significant challenges when building TTS and ASR systems for extremely low-resource languages.
no code implementations • 2 Jul 2020 • Bin Zhang, Jian Li, Yabiao Wang, Zhipeng Cui, Yili Xia, Chengjie Wang, Jilin Li, Feiyue Huang
Cartoon face detection is a more challenging task than human face detection due to many difficult scenarios is involved.
no code implementations • 18 Jun 2020 • Jian Li, Yong liu, Jiankun Liu, Weiping Wang
The encoder and the decoder belong to a graph VAE, mapping architectures between continuous representations and network architectures.
no code implementations • NeurIPS 2020 • Yuanhao Wang, Jian Li
This paper studies minimax optimization problems $\min_x \max_y f(x, y)$, where $f(x, y)$ is $m_x$-strongly convex with respect to $x$, $m_y$-strongly concave with respect to $y$ and $(L_x, L_{xy}, L_y)$-smooth.
no code implementations • 11 Jun 2020 • Chuheng Zhang, Yuanying Cai, Longbo Huang, Jian Li
In the planning phase, the agent computes a good policy for any reward function based on the dataset without further interacting with the environment.
no code implementations • 25 Mar 2020 • Bin Zhang, Jian Li, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yili Xia, Wenjiang Pei, Rongrong Ji
In this paper, we propose a novel Automatic and Scalable Face Detector (ASFD), which is based on a combination of neural architecture search techniques as well as a new loss design.
no code implementations • 3 Mar 2020 • Qichen Li, Yuanqing Lin, Luofeng Zhou, Jian Li
Creating meta-embeddings for better performance in language modelling has received attention lately, and methods based on concatenation or merely calculating the arithmetic mean of more than one separately trained embeddings to perform meta-embeddings have shown to be beneficial.
no code implementations • 28 Feb 2020 • Jian Li, Yong liu, Weiping Wang
Recently, non-stationary spectral kernels have drawn much attention, owing to its powerful feature representation ability in revealing long-range correlations and input-dependent characteristics.
no code implementations • 25 Feb 2020 • Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini
Nowadays, devices are equipped with advanced sensors with higher processing/computing capabilities.
no code implementations • 20 Feb 2020 • Qilin Fan, Xiuhua Li, Jian Li, Qiang He, Kai Wang, Junhao Wen
Compared to the conventional content delivery networks, caches in edge networks with smaller sizes usually have to accommodate more bursty requests.
1 code implementation • NeurIPS 2020 • Shufan Wang, Jian Li, Shiqiang Wang
We obtain both deterministic and randomized online algorithms with provably improved performance when either a single or multiple ML predictions are used to make decisions.
no code implementations • 9 Feb 2020 • Tianping Zhang, Yuanqi Li, Yifei Jin, Jian Li
The multi-factor model is a widely used model in quantitative investment.
3 code implementations • 16 Jan 2020 • Silei Xu, Giovanni Campagna, Jian Li, Monica S. Lam
The key concept is to cover the space of possible compound queries on the database with a large number of in-domain questions synthesized with the help of a corpus of generic query templates.
no code implementations • 22 Nov 2019 • Jian Li, Xing Wang, Baosong Yang, Shuming Shi, Michael R. Lyu, Zhaopeng Tu
Starting from this intuition, we propose a novel approach to compose representations learned by different components in neural machine translation (e. g., multi-layer networks or multi-head attention), based on modeling strong interactions among neurons in the representation vectors.
3 code implementations • 11 Nov 2019 • Chuming Lin, Jian Li, Yabiao Wang, Ying Tai, Donghao Luo, Zhipeng Cui, Chengjie Wang, Jilin Li, Feiyue Huang, Rongrong Ji
In this paper, we propose an efficient and unified framework to generate temporal action proposals named Dense Boundary Generator (DBG), which draws inspiration from boundary-sensitive methods and implements boundary classification and action completeness regression for densely distributed proposals.
no code implementations • 25 Oct 2019 • Jian Li, Yan Wang, Xiubao Zhang, Weihong Deng, Haifeng Shen
In this paper, we train a validation classifier to normalize the decision threshold, which means that the result can be obtained directly without replacing the threshold.
no code implementations • 26 Sep 2019 • Yuan Shangguan, Jian Li, Qiao Liang, Raziel Alvarez, Ian McGraw
While most deployed speech recognition systems today still run on servers, we are in the midst of a transition towards deployments on edge devices.
1 code implementation • 11 Sep 2019 • Jian Li, Yong liu, Weiping Wang
The generalization performance of kernel methods is largely determined by the kernel, but common kernels are stationary thus input-independent and output-independent, that limits their applications on complicated tasks.
1 code implementation • 11 Sep 2019 • Jian Li, Yong liu, Weiping Wang
Vector-valued learning, where the output space admits a vector-valued structure, is an important problem that covers a broad family of important domains, e. g. multi-label learning and multi-class classification.
1 code implementation • 3 Aug 2019 • Jie Tang, Fei-Peng Tian, Wei Feng, Jian Li, Ping Tan
It is thus necessary to complete the sparse LiDAR data, where a synchronized guidance RGB image is often used to facilitate this completion.
1 code implementation • 26 Jun 2019 • Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang
Previous research shows that 1) popular network embedding benchmarks, such as DeepWalk, are in essence implicitly factorizing a matrix with a closed form, and 2)the explicit factorization of such matrix generates more powerful embeddings than existing methods.
no code implementations • (IJCAI 2019 • Li Zheng, Zhenpeng Li, Jian Li, Zhao Li, and Jun Gao
Anomaly detection in dynamic graphs becomes very critical in many different application scenarios, e. g., recommender systems, while it also raises huge challenges due to the high flexible nature of anomaly and lack of sufficient labelled data.
1 code implementation • ICLR 2020 • Kaifeng Lyu, Jian Li
In this paper, we study the implicit regularization of the gradient descent algorithm in homogeneous neural networks, including fully-connected and convolutional neural networks with ReLU or LeakyReLU activations.
1 code implementation • 7 Jun 2019 • Jian Li, Yong liu
In this paper, using refined proof techniques, we first extend the optimal rates for distributed learning with random features to the non-attainable case.
1 code implementation • NAACL 2019 • Jianhao Yan, Lin He, Ruqin Huang, Jian Li, Ying Liu
This paper formulates the problem of relation extraction with temporal reasoning and proposes a solution to predict whether two given entities participate in a relation at a given time spot.
no code implementations • 27 May 2019 • Chuheng Zhang, Yuanqi Li, Jian Li
We observe that several existing policy gradient methods (such as vanilla policy gradient, PPO, A2C) may suffer from overly large gradients when the current policy is close to deterministic (even in some very simple environments), leading to an unstable training process.
no code implementations • 23 May 2019 • Haleh Akrami, Anand A. Joshi, Jian Li, Sergul Aydore, Richard M. Leahy
Machine learning methods often need a large amount of labeled training data.
no code implementations • 3 May 2019 • Xuan Cao, Yanhao Ge, Ying Tai, Wei zhang, Jian Li, Chengjie Wang, Jilin Li, Feiyue Huang
In this work, we propose a novel framework named Region-Aware Network (RANet), which learns the ability of anti-confusing in case of heavy occlusion, nearby person and symmetric appearance, for human pose estimation.
no code implementations • 6 Apr 2019 • Ali Sadeghian, Deoksu Lim, Johan Karlsson, Jian Li
The use of distances based on optimal transportation has recently shown promise for discrimination of power spectra.
no code implementations • NAACL 2019 • Jian Li, Baosong Yang, Zi-Yi Dou, Xing Wang, Michael R. Lyu, Zhaopeng Tu
Multi-head attention is appealing for its ability to jointly extract different types of information from multiple representation subspaces.
no code implementations • 1 Mar 2019 • Eryu Xia, Xin Du, Jing Mei, Wen Sun, Suijun Tong, Zhiqing Kang, Jian Sheng, Jian Li, Changsheng Ma, Jian-Zeng Dong, Shaochun Li
The results demonstrate cluster analysis using outcome-driven multi-task neural network as promising for patient classification and subtyping.
no code implementations • 15 Feb 2019 • Baosong Yang, Jian Li, Derek Wong, Lidia S. Chao, Xing Wang, Zhaopeng Tu
Self-attention model have shown its flexibility in parallel computation and the effectiveness on modeling both long- and short-term dependencies.
no code implementations • 13 Feb 2019 • Yong Liu, Jian Li, Guangjun Wu, Lizhong Ding, Weiping Wang
In this paper, we provide a method to approximate the CV for manifold regularization based on a notion of robust statistics, called Bouligand influence function (BIF).
no code implementations • ICLR 2020 • Jian Li, Xuanyuan Luo, Mingda Qiao
We develop a new framework, termed Bayes-Stability, for proving algorithm-dependent generalization error bounds.
no code implementations • 19 Dec 2018 • Yong Liu, Jian Li, Weiping Wang
We study the risk performance of distributed learning for the regularization empirical risk minimization with fast convergence rate, substantially improving the error analysis of the existing divide-and-conquer based distributed learning.
no code implementations • 13 Dec 2018 • Kun Tu, Jian Li, Don Towsley, Dave Braines, Liam Turner
In this paper, we explore the role of \emph{graphlets} in network classification for both static and temporal networks.
no code implementations • NeurIPS 2018 • Jian Li, Yong liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang
In this paper, we study the generalization performance of multi-class classification and obtain a shaper data-dependent generalization error bound with fast convergence rate, substantially improving the state-of-art bounds in the existing data-dependent generalization analysis.
3 code implementations • CVPR 2019 • Jian Li, Yabiao Wang, Changan Wang, Ying Tai, Jianjun Qian, Jian Yang, Chengjie Wang, Jilin Li, Feiyue Huang
In this paper, we propose a novel face detection network with three novel contributions that address three key aspects of face detection, including better feature learning, progressive loss design and anchor assign based data augmentation, respectively.
Ranked #1 on
Face Detection
on FDDB
no code implementations • EMNLP 2018 • Jian Li, Zhaopeng Tu, Baosong Yang, Michael R. Lyu, Tong Zhang
Multi-head attention is appealing for the ability to jointly attend to information from different representation subspaces at different positions.
no code implementations • 27 Sep 2018 • Sahisnu Mazumder, Bing Liu, Shuai Wang, Yingxuan Zhu, Xiaotian Yin, Lifeng Liu, Jian Li, Yongbing Huang
This paper proposes a new method to drastically speed up deep reinforcement learning (deep RL) training for problems that have the property of \textit{state-action permissibility} (SAP).
1 code implementation • CVPR 2019 • Zhen He, Jian Li, Daxue Liu, Hangen He, David Barber
To achieve both label-free and end-to-end learning of MOT, we propose a Tracking-by-Animation framework, where a differentiable neural model first tracks objects from input frames and then animates these objects into reconstructed frames.
no code implementations • 7 Sep 2018 • Zhize Li, Jian Li
Besides, if the hyperparameters (e. g., the Lipschitz smooth parameter $L$) are not available, we propose a guessing algorithm for guessing them dynamically and also prove a similar convergence rate.
no code implementations • 10 Jul 2018 • Kun Tu, Jian Li, Don Towsley, Dave Braines, Liam D. Turner
Network classification has a variety of applications, such as detecting communities within networks and finding similarities between those representing different aspects of the real world.
3 code implementations • NeurIPS 2018 • Wei Cao, Dong Wang, Jian Li, Hao Zhou, Lei LI, Yitan Li
It is ubiquitous that time series contains many missing values.
General Classification
Multivariate Time Series Forecasting
+2
no code implementations • 29 Mar 2018 • Zhize Li, Tianyi Zhang, Shuyu Cheng, Jun Zhu, Jian Li
In this paper, we apply the variance reduction tricks on Hamiltonian Monte Carlo and achieve better theoretical convergence results compared with the variance-reduced Langevin dynamics.
1 code implementation • 15 Feb 2018 • Yu Shi, Jian Li, Zhize Li
We show that PL Trees can accelerate convergence of GBDT and improve the accuracy.
no code implementations • NeurIPS 2018 • Zhize Li, Jian Li
In particular, ProxSVRG+ generalizes the best results given by the SCSG algorithm, recently proposed by [Lei et al., 2017] for the smooth nonconvex case.
1 code implementation • 27 Nov 2017 • Jian Li, Yue Wang, Michael R. Lyu, Irwin King
Intelligent code completion has become an essential research task to accelerate modern software development.
4 code implementations • 9 Oct 2017 • Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang
This work lays the theoretical foundation for skip-gram based network embedding methods, leading to a better understanding of latent network representation learning.
no code implementations • 28 Sep 2017 • Jianbo Guo, Guangxiang Zhu, Jian Li
They fit generative models by minimizing certain distance measure between the real image distribution and the generated data distribution.
no code implementations • 4 Jun 2017 • Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang
We provide a novel instance-wise lower bound for the sample complexity of the problem, as well as a nontrivial sampling algorithm, matching the lower bound up to a factor of $\ln|\mathcal{F}|$.
no code implementations • 20 May 2017 • Yifei Jin, Lingxiao Huang, Jian Li
Our algorithms achieve $(1-\epsilon)$-approximations with running time $\tilde{O}(nd+n\sqrt{d / \epsilon})$ for both variants, where $n$ is the number of points and $d$ is the dimensionality.
no code implementations • 19 May 2017 • Haotian Jiang, Jian Li, Mingda Qiao
In the Best-$K$ identification problem (Best-$K$-Arm), we are given $N$ stochastic bandit arms with unknown reward distributions.
1 code implementation • 25 Apr 2017 • Wenjian Yu, Yu Gu, Jian Li, Shenghua Liu, Yaohang Li
Principal component analysis (PCA) is a fundamental dimension reduction tool in statistics and machine learning.
2 code implementations • ICML 2017 • Kaifeng Lv, Shunhua Jiang, Jian Li
Training deep neural networks is a highly nontrivial task, involving carefully selecting appropriate training algorithms, scheduling step sizes and tuning other hyperparameters.
no code implementations • 13 Feb 2017 • Lijie Chen, Jian Li, Mingda Qiao
In the Best-$k$-Arm problem, we are given $n$ stochastic bandit arms, each associated with an unknown reward distribution.
no code implementations • 30 Oct 2016 • Keyu Lu, Jian Li, Xiangjing An, Hangen He
This paper presents a generalized Haar filter based deep network which is suitable for the object detection tasks in traffic scene.
2 code implementations • 26 Oct 2016 • Zhize Li, Jian Li, Hongwei Huo
The open problem asked to design in-place algorithms in $o(n\log n)$ time and ultimately, in $O(n)$ time for (read-only) integer alphabets with $|\Sigma| \leq n$.
Data Structures and Algorithms
no code implementations • NeurIPS 2016 • Wei Chen, Wei Hu, Fu Li, Jian Li, Yu Liu, Pinyan Lu
Our framework enables a much larger class of reward functions such as the $\max()$ function and nonlinear utility functions.
no code implementations • 22 Aug 2016 • Lijie Chen, Jian Li, Mingda Qiao
$H(I)=\sum_{i=2}^n\Delta_{[i]}^{-2}$ is the complexity of the instance.
1 code implementation • 13 Jul 2016 • Weishan Dong, Jian Li, Renjie Yao, Changsheng Li, Ting Yuan, Lanjun Wang
Characterizing driving styles of human drivers using vehicle sensor data, e. g., GPS, is an interesting research problem and an important real-world requirement from automotive industries.
no code implementations • 12 Jun 2016 • Mengwen Xu, Tianyi Wang, Zhengwei Wu, Jingbo Zhou, Jian Li, Haishan Wu
In this paper, we propose a Demand Distribution Driven Store Placement (D3SP) framework for business store placement by mining search query data from Baidu Maps.
no code implementations • 27 May 2016 • Lijie Chen, Jian Li
The best arm identification problem (BEST-1-ARM) is the most basic pure exploration problem in stochastic multi-armed bandits.
no code implementations • 23 May 2016 • Lijie Chen, Anupam Gupta, Jian Li
In a Best-Basis instance, we are given $n$ stochastic arms with unknown reward distributions, as well as a matroid $\mathcal{M}$ over the arms.
no code implementations • 6 May 2016 • Jian Li, Martin Levine, Xiangjing An, Xin Xu, Hangen He
First, we consider saliency detection as a frequency domain analysis problem.
no code implementations • NeurIPS 2015 • Tian Lin, Jian Li, Wei Chen
We further show that the bound is tight in $T$ and other problem instance parameters.
no code implementations • NeurIPS 2015 • Wei Cao, Jian Li, Yufei Tao, Zhize Li
This paper discusses how to efficiently choose from $n$ unknowndistributions the $k$ ones whose means are the greatest by a certainmetric, up to a small relative error.
no code implementations • 12 Nov 2015 • Lijie Chen, Jian Li
The $i$th arm has a reward distribution $D_i$ with an unknown mean $\mu_{i}$.
no code implementations • 10 Apr 2015 • Jian Li, Yuval Rabani, Leonard J. Schulman, Chaitanya Swamy
We study the problem of learning from unlabeled samples very general statistical mixture models on large finite sets.
1 code implementation • 4 Jan 2013 • Danny Z. Chen, Jian Li, Hongyu Liang, Haitao Wang
We also consider the outlier version of the problem where a given number of vertices can be excluded as the outliers from the solution.
Data Structures and Algorithms Discrete Mathematics
no code implementations • NeurIPS 2007 • Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu, Hang Cui, Edward Y. Chang
Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time.