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Adaptive Regret of Convex and Smooth Functions

@InProceedings{pmlr-v97-zhang19j, title = {Adaptive Regret of Convex and Smooth Functions}, author = {Zhang, Lijun and Liu, Tie-Yan and Zhou, Zhi-Hua}, booktitle = {Proceedings of the 36th International Conference on Machine Learning}, pages = {7414--7423}, year = {2019}, editor = {Chaudhuri, Kamalika and Salakhutdinov, Ruslan}, volume = {97}, series = {Proceedings of Machine Learning Research ...

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Rockwell scale - Wikipedia

The Rockwell scale is a hardness scale based on indentation hardness of a material. The Rockwell test measuring the depth of penetration of an indenter under a large load (major load) compared to the penetration made by a preload (minor load). There are different scales, denoted by a single letter, that use different loads or indenters.

Lijun Zhang's NJU Homepage

Lijun Zhang (张利军) I am an associate professor of the Dept. of Computer Science and Technology, Nanjing University. I am also a member of the LAMDA group. Email: zljzju at gmail.com zlj at nju.edu.cn Mail: Nanjing University, Xianlin Campus Mailbox 603 163 Xianlin Avenue, Qixia District Nanjing 210023, China Office: Room 310, Computer Science Building, Xianlin Campus Phone: +86-25-89680949

convex - definiție și paradigmă | dexonline

Dicționar dexonline. Definiții, sinonime, antonime, conjugări, declinări, paradigme pentru convex din dicționarele: DEX '09, DEX '98, MDA2, DLRLC, DN, MDN '00 ...

[1904.11681] Adaptive Regret of Convex and Smooth Functions

Authors: Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou (Submitted on 26 Apr 2019 , last revised 9 May 2019 (this version, v2)) Abstract: We investigate online convex optimization in changing environments, and choose the adaptive regret as the performance measure. The goal is to achieve a small regret over every interval so that the comparator is allowed to change over time. Different from previous ...

Adaptive Online Learning in Dynamic Environments

Lijun Zhang, Shiyin Lu, Zhi-Hua Zhou National Key Laboratory for Novel Software Technology Nanjing University, Nanjing 210023, China {zhanglj, lusy, zhouzh}@lamda.nju.edu.cn Abstract In this paper, we study online convex optimization in dynamic environments, and aim to bound the dynamic regret with respect to any sequence of comparators. Existing work have shown that online gradient descent ...

get_region_convex [HALCON Operator Reference / Version 12.0.2]

Description. The operator get_region_convex returns the convex hull of a region as polygon. The polygon is the minimum result of line (Rows) and column coordinates (Columns) describing the hull of the region.The polygon pixels lie on the region. The polygon starts at the smallest line number; in this line at the pixel with the largest column index.

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Lijun Zhang | DeepAI

Bandit Convex Optimization (BCO) is a fundamental framework for modeling... 07/29/2019 ∙ by Peng Zhao, et al. ∙ 4 ∙ share read it. Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions To deal with changing environments, a new performance measure---adaptive... 06/26/2019 ∙ by Lijun Zhang, et al. ∙ 2 ∙ share read it. Multi-Objective ...

Tianbao Yang's homepage

with Lijun Zhang, Mehrdad Mahdavi, Rong Jin and Shenghuo Zhu In COLT, 2013. O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions with Lijun Zhang, Rong Jin and Xiaofei He In ICML, 2013. Robust Ensemble Clustering by Matrix Completion Jinfeng Yi, Tianbao Yang, Rong Jin, Anil Jain In ICDM, 2012.

杨利军-数学与统计学院网站 - henu.edu.cn

[7] Lijun Yang, Zhihua Yang, Feng Zhou and Lihua Yang. A Novel Envelope Model Based On Convex Constrained Optimization. Digital Signal Processing, 2014, 29:138-146 . [8] Lijun Yang, Zhihua Yang, Lihua Yang and Ping Zhang. An improved envelope algorithm for eliminating undershoot . Digital Signal Processing, 2013, 23:401-411 . 科研项目:

ICML Beijing

convex. Download Pic. Lijun Zhang and Jinfeng Yi and Rong Jin. Efficient Algorithms for Robust One-bit Compressive Sensing (pdf) While the conventional compressive sensing assumes measurements of infinite precision, one-bit compressive sensing considers an extreme setting where each measurement is quantized to just a single bit. In this paper, we study the vector recovery problem from noisy ...

Spectral Frank-Wolfe Algorithm: Strict Complementarity and ...

Lijun Ding, Yingjie Feiy, Qiantong Xu z, and Chengrun Yang x July 1, 2020 Abstract We develop a novel variant of the classical Frank-Wolfe algorithm, which we call spectral Frank-Wolfe, for convex optimization over a spectrahedron. The spectral Frank-Wolfe algorithm has a novel ingredient: it computes a few eigenvectors of the gradient and solves a small-scale SDP in each iteration. Such ...

[PDF] Empirical Risk Minimization for Stochastic Convex ...

Although there exist plentiful theories of empirical risk minimization (ERM) for supervised learning, current theoretical understandings of ERM for a related problem---stochastic convex optimization (SCO), are limited. In this work, we strengthen the realm of ERM for SCO by exploiting smoothness and strong convexity conditions to improve the risk bounds.

Lijun Zhang Resume - Nanjing University

Convex Optimization with O(p T) Communication Complexity. In Proceedings of the 37th International Conference on Machine Learning (ICML), to appear, 2020. 2.Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, and Tianbao Yang. Stochastic Opti-mization for Non-convex Inf-Projection Problems. In Proceedings of the 37th Inter-national Conference on Machine Learning (ICML), to appear, 2020. 3.Bo Xue ...

Lijun Chen's Page - University of Colorado Boulder

Lijun Chen Department of Computer Science University of Colorado at Boulder Boulder, CO 80309-0430 Office: ECCR 1B12 Tel: 303-492-4384 Fax: 303-492-1112 Email: lijun.chen[at]colorado.edu. I am an Assistant Professor of Computer Science at the University of Colorado at Boulder. I did my doctoral work at the California Institute of Technology, and was a Research Scientist at the same institute ...

Paper - proceedings.icml.cc

Yan Yan, Yi Xu, Lijun Zhang, Wang Xiaoyu, Tianbao Yang. Abstract. In this paper, we study a family of non-convex and possibly non-smooth inf-projection minimization problems, where the target objective function is equal to minimization of a joint function over another variable. This problem include difference of convex (DC) functions and a family of bi-convex functions as special cases. We ...

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arXiv:2010.08177v1 [cs.LG] 16 Oct 2020

Projection-free Online Learning over Strongly Convex Sets Yuanyu Wan, Lijun Zhang National Key Laboratoryfor Novel Software Technology, Nanjing University,Nanjing 210023,China wanyy@lamda.nju.edu.cn,zhanglj@lamda.nju.edu.cn Abstract To efficiently solve online problems with complicated con-straints, projection-free algorithms including online frank- wolfe (OFW) and its variants have received ...

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Lijun Ding| Cornell ORIE

I am a fifth year Ph.D. student in the School of Operations Research and Information Engineering at Cornell University. I am advised by Prof. Yudong Chen and Prof. Madeleine Udell.Prior to joining Cornell in the Fall of 2016, I graduated with a Master of Science in Statistics from the University of Chicago advised by Prof. Lek-Heng Lim .I received a Bachelor of Science in Mathematics and ...

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Lijun Ding Yudong Chen arXiv:1911.05774v2 [cs.LG] 18 Nov 2019

Lijun Ding Cornell University Ithaca, NY 14850 ld446@cornell.edu Yudong Chen Cornell University Ithaca, NY 14850 yudong.chen@cornell.edu Madeleine Udell Cornell University Ithaca, NY 14850 udell@cornell.edu Abstract This paperdevelopsa new class of nonconvexregularizersforlow-rankmatrix re-covery. Many regularizers are motivated as convex relaxations of the matrix rank function ...

Yudong Chen - Cornell University

Congratulations to my student Lijun Ding for winning the 2019 Student Paper Prize of INFORMS Optimization Society. ... Convex Relaxation Methods for Community Detection Xiaodong Li, Yudong Chen, and Jiaming Xu. Statistical Science, 2019. Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin, Yudong Chen, Kannan Ramchandran, and Peter Bartlett. International ...

Lijun Zhang's research works | Nanjing University, Nanjing ...

Lijun Zhang's 14 research works with 82 citations and 242 reads, including: Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions

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convex - LEO: Übersetzung im Englisch ⇔ Deutsch Wörterbuch

Lernen Sie die Übersetzung für 'convex' in LEOs Englisch ⇔ Deutsch Wörterbuch. Mit Flexionstabellen der verschiedenen Fälle und Zeiten Aussprache und relevante Diskussionen Kostenloser Vokabeltrainer

王立军 Wang Lijun's research works

王立军 Wang Lijun's 35 research works with 75 citations and 212 reads, including: High-Brightness 800-nm Semiconductor Laser Source Based on Spectral Beam Combining

LijunZhang zlj@nju.edu.cn http://cs.nju.edu.cn/zlj

a convex cone if its base 4is 0. Any subspace is affine, and a convex cone (hence convex). Some Examples. Hyperplanes á, and Other Forms 4is any point such that 𝑎 C𝑥 4𝑏 C C 4. Hyperplanes á, and Other Forms 4is any point such that 𝑎 C𝑥 4𝑏 D C C 4 4 D C C 4. Halfspaces á, and Other Forms 4is any point such that 𝑎 C𝑥 4𝑏 Convex Not affine C C 4. Balls Definition ...

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Lijun ZHANG | Beihang University (BUAA), Beijing | BUAA ...

Lijun ZHANG of Beihang University (BUAA), Beijing (BUAA) | Read 89 publications | Contact Lijun ZHANG

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ICML | 2018

Tianbao Yang · Qihang Lin · Lijun Zhang 2017 Talk: A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates » Tianbao Yang · Qihang Lin · Lijun Zhang 2017 Talk: Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence »

ICML | 2019

We investigate online convex optimization in changing environments, and choose the adaptive regret as the performance measure. The goal is to achieve a small regret over every interval so that the comparator is allowed to change over time. Different from previous works that only utilize the convexity condition, this paper further exploits smoothness to improve the adaptive regret. To this end ...

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dblp: Adaptive Regret of Convex and Smooth Functions.

Bibliographic details on Adaptive Regret of Convex and Smooth Functions. In view of the current Corona Virus epidemic, Schloss Dagstuhl has moved its 2020 proposal submission period to July 1 to July 15, 2020 , and there will not be another proposal round in November 2020.

ICML | 2020

2020 Poster: Stochastic Optimization for Non-convex Inf-Projection Problems » Yan Yan · Yi Xu · Lijun Zhang · Wang Xiaoyu · Tianbao Yang 2019 Poster: Adaptive Regret of Convex and Smooth Functions » Lijun Zhang · Tie-Yan Liu · Zhi-Hua Zhou 2019 Oral: Adaptive Regret of Convex and Smooth Functions »

Lijun Zhang's research works | Nanjing University, Nanjing ...

Lijun Zhang's 14 research works with 77 citations and 233 reads, including: Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions

Lijun Chen's research works | University of Colorado ...

Lijun Chen's 14 research works with 108 citations and 555 reads, including: Utilizing Players' In-game Time Spending Records for Churn Prediction: Mining In-game Time Spending Regularity

dblp: Shiyin Lu

proposal submission period to July 1 to July 15, 2020, and there will not be another proposal round in November 2020. Please consider submitting your proposal for future Dagstuhl Seminars & Workshops.For more information, see our Call for Proposals.

ICML | 2020

Yan Yan · Yi Xu · Lijun Zhang · Wang Xiaoyu · Tianbao Yang. Tue Jul 14 07:00 AM -- 07:45 AM & Tue Jul 14 06:00 PM -- 06:45 PM (PDT) @ None #None in Poster Session 1 » In this paper, we study a family of non-convex and possibly non-smooth inf-projection minimization problems, where the target objective function is equal to minimization of a joint function over another variable. This ...

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