A Burden Shared is a Burden Halved: A Fairness-Adjusted Approach to Classification
14:00
Talk & Lecture
1
2884705
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2024-03-04
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Speaker: Bradley Rava, Lecturer, University of SydneyTime: 14:00, March 15Venue: Room 1417, Administrative Building, Zijingang CampusAbstract: We investigate fairness in classification, where automated decisions are made for individuals from different protected groups. In high-consequence scenarios, decision errors can disproportionately affect certain protected groups, leading to unfair outcomes. To address this issue, we propose a fairness-adjusted selective inference (FASI) framework and develop data-driven algorithms that achieve statistical parity by controlling and equalizing the false selection rate (FSR) among protected groups. Our FASI algorithm operates by converting the outputs of black-box classifiers into R-values, which are both intuitive and computationally efficient. The selection rules based on R-values, which effectively mitigate disparate impacts on protected groups, are provably valid for FSR control in finite samples. We demonstrate the numerical performance of our approach through both simulated and real data.Bio: Brad Rava is a Lecturer in the discipline of Business Analytics at the University of Sydney's Business School. His research focuses on Empirical Bayes techniques, Fairness in Machine Learning, Statistical Machine Learning, and High Dimensional Statistics. Brad Rava’s research interests focus modern statistical methods for addressing pressing societal problems that arise from combining automated decision making with high-risk scenarios. To properly communicate uncertainty in these high-risk scenarios, Brad’s research has drawn upon Empirical Bayes techniques, Fairness in Machine Learning, Statistical Machine Learning, and High Dimensional Statistics.
We propose a fairness-adjusted selective inference (FASI) framework and develop data-driven algorithms that achieve statistical parity by controlling and equalizing the false selection rate (FSR) among protected groups.
Bradley Rava
2024-03-15 17:07:38
Zijingang Campus
Preconditioned Riemannian Gradient Descent for Low-Rank Matrix Recovery Problems
10:00
Talk & Lecture
2
2884699
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2024-03-04
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Speaker: Prof. Jianfeng CAI, Hong Kong University of Science and TechnologyTime: 10:00, March 11Venue: Room 1417, Administrative Building, Zijingang CampusAbstract: The challenge of recovering low-rank matrices from linear samples is a common issue in various fields, including machine learning, imaging, signal processing, and computer vision. Non-convex algorithms have proven to be highly effective and efficient for low-rank matrix recovery, providing theoretical guarantees despite the potential for local minima. This talk presents a unifying framework for non-convex low-rank matrix recovery algorithms using Riemannian gradient descent. We demonstrate that numerous well-known non-convex low-rank matrix recovery algorithms can be considered special instances of Riemannian gradient descent, employing distinct Riemannian metrics and retraction operators. Consequently, we can pinpoint the optimal metrics and develop the most efficient non-convex algorithms. To illustrate this, we introduce a new preconditioned Riemannian gradient descent algorithm, which accelerates matrix completion tasks by more than ten times compared to traditional methods.
This talk presents a unifying framework for non-convex low-rank matrix recovery algorithms using Riemannian gradient descent.
Jianfeng CAI
2024-03-11 16:44:19
Zijingang Campus
Statistical inference for high-dimensional regression with proxy data
14:00
Talk & Lecture
3
2884643
/english/2024/0304/c19936a2884643/page.psp
2024-03-04
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Speaker: Associate professor LI Sai, Renmin University of ChinaTime: 14:00, March 8Venue: Room 1417, Administrative Building, Zijingang CampusAbstract: We study estimation and inference for high-dimensional linear models with two types of “proxy data”. The first type of proxies encompasses marginal statistics and sample covariance matrices computed from distinct sets of individuals. We develop a rate optimal method for estimation and inference for the regression coefficient vector and its linear functionals based on the proxy data. We show the intrinsic limitations in the proxy-data based inference: the minimax optimal rate for estimation is slower than that in the conventional case where individual data are observed. The second type of proxy data is differentially private data. We propose method for private estimation and inference in high-dimensional regression with FDR control.
We study estimation and inference for high-dimensional linear models with two types of “proxy data”.
LI Sai
2024-03-08 14:00:00
Zijingang Campus
Ricci flow and pinched curvature on noncompact manifold
16:15-17:15
Talk & Lecture
4
2881807
/english/2024/0228/c19936a2881807/page.psp
2024-02-28
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Speaker: Prof. Man Chun LEE, The Chinese University of Hong KongTime: 16:15-17:15, Feb. 28Venue: Room 101, No.2 Building, Haina Complex Building 2, Zijingang CampusAbstract: In this talk, we will discuss some recent development of Ricci flow existence on complete noncompact manifolds. In particular, we will discuss applications on manifold with curvature pinching.
In this talk, we will discuss some recent development of Ricci flow existence on complete noncompact manifolds. In particular, we will discuss applications on manifold with curvature pinching.
Man Chun LEE
2024-02-28 10:11:43
Zijingang Campus
Serendipity in science: a story on O2 sensors and fibroblasts in vascular health and disease
10:30
Talk & Lecture
5
2881926
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2024-02-27
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Speaker: Judith Sluimer, Professor, Principle Investigator Experimental Vascular Pathology group, Maastricht UniversityVenue: Room 245, the College of Life Sciences, Zijingang Campus_Judith SluimerVenue_ Room 245, the
Judith Sluimer, Professor, Principle Investigator Experimental Vascular Pathology group, Maastricht University
Judith Sluimer
2024-02-28 15:41:39
Zijingang Campus
100 years of the Schur-Weyl Duality
10:00
Talk & Lecture
6
2859593
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2024-01-16
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Speaker: Prof. DU Jie (The University of New South Wales)Venue: Room 210, Building 2, Haina Court, Zijingang CampusNote: Please scan the QR code in the picture above to register.
I will discuss Schur-Weyl Duality's latest developments from its quantum version in late 80s to the affine/super analoques and its recent generalization to tvpes other than A via quantum symmetric pairs and i-quantum groups. I will also mention the contributions by three groups of Chinese mathematicians.
2024-01-27 10:00:00
Room 210, Building 2, Haina Court, Zijingang Campus
How to leverage your time and exposure in ZIBS to harness future opportunities
11:00-12:00
Talk & Lecture
7
2859427
/english/2024/0116/c19936a2859427/page.psp
2024-01-16
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Speaker: Koh Chaik Ming, Senior Research Fellow at National University of Singapore, Adjunct Professor at Singapore Management University and Nanyang Technological University.Venue: Room 359, ZIBS Building, Haining CampusLanguage: BilingualNote: Please scan the QR code in the picture above to register.
Koh Chaik Ming, Senior Research Fellow at National University of Singapore, will deliver a lecture on how to leverage the time and exposure in ZIBS to harness future opportunities in ZIBS Caeer Talk series. Welcome to participate!
2024-01-16 11:00:00
Room 359, ZIBS Building, Haining Campus
Chinese Companies Going Global in the New Era
18:30-19:30
Talk & Lecture
8
2859603
/english/2024/0116/c19936a2859603/page.psp
2024-01-15
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Speaker: HUANG Yuanpu (Yuan), EqualOcean Founding PartnerVenue: Room 357/359, ZIBS Building, Haining CampusNote: Please scan the QR code in the picture above to register.
HUANG Yuanpu (Yuan), Founding Partner EqualOcean, will share his perspectives on "Chinese Companies Going Global in the New Era". Welcome to participate!
2024-01-12 18:30:00
Room 357/359, ZIBS Building, Haining Campus
Partition, Power Sharing and Peace: A Spatial Analysis
15:00-16:30
Talk & Lecture
9
2857505
/english/2024/0110/c19936a2857505/page.psp
2024-01-10
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Presenter: Lars-Erik Cederman (member of the German National Academy of Sciences)Discussant: Prof. Kurtuluş Gemici, Prof. Andre PythonVenue: Room 1127, Block A, Creative Building, West Zone, Zijingang CampusAbstract:Does the partitioning of states along ethnic lines reduce conflict? While theorists drawing on the “security dilemma” argue that partition prevents conflict recurrence by separating the parties, others dispute these findings. Advancing in four analytical steps, this work first reconceptualize partition as decreased cohabitation in dyads between transnationally defined ethnic groups. Based on a global dataset (1945-2017), we find that whereas complete partition reduces internal conflict, its incomplete application increases this risk. The second step adopts a nationalist logic and tests whether partition reduces conflict if it eliminates dyadic domination. Third, the analysis focuses on whether reduced domination makes civil conflict less likely, with or without border change. We show that power sharing can be at least as effective in reducing domination as partition. The fourth and final step investigates the various side effects of state splits on both civil and interstate conflict. Generally, we find that partition may fuel instability both within and outside the dyad.
Advancing in four analytical steps, this work first reconceptualize partition as decreased cohabitation in dyads between transnationally defined ethnic groups.
2024-01-10 15:00:00
Room 1127, Block A, Creative Building, West Zone, Zijingang Campus