On Generalization and Implicit Bias of Gradient Methods in Deep Learning (KAUST 2019,NJU 2019,HUJI 2019,BASICS 2019,HKUST 2019,SANYA AI conference 2019,Foushan CSIAM 19,智能计算机大会 2019, Damo 2020,IJTCS 2020) [slides]

深度学习的理论基础:非凸学习的优化与泛化 (高技术领域学者沙龙 2019 人工智能对数学的期待) [slides]

深度学习与在线学习理论 (CCF启智会2019:大数据与人工智能中的基础理论)[slides]

Learning and Prediction over Massive Spatio-temporal Data [Jingdong 2017, Shanshu 2018,Huawei 2018, Nanjing Turing Institute 2018] [slides]

Coresets for Clustering (with Outliers) in Doubling Metrics (NCTCS 2018,Turing Forum (PKU-SJTU-THU) 2019)[slides]

A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization (MSRA 2018)[slides]

Stochastic Combinatorial Optimization (FAW 2019) [slides]

Approximation Algorithms for Stochastic Geometric Optimization Problems (C&A 2017) [slides]

Stochastic Online Optimization (CNCC 2016, Taiyuan) [slides]

Online Learning and Multi-armed Bandits(Utah 2016, NDBC2016 Shenzhen) [slides]

On optimal sampling complexity for combinatorial multi-armed bandits (2017 北工大最优化发展研讨会, Fudan 2017, shufe 2017)

Pure Exploration of Stochastic Multi-armed Bandits (Hangzhou C&A, ICT 2015, AMSS CAS Beijing 16 2016) [slides]

Algorithms for Stochastic Geometric and Combinatorial Optimization Problems (CAS Beijing 15, Haifa 2016) [slides]

Learning Arbitrary Statistical Mixtures of Discrete Distributions (STOC 2015, CAS Beijing 15) [slides]

Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing (ICML 2014, ICML crowdsourcing workshop 2014) [slides]

Multi-armed bandit problems (WAIM 2014, Macau, distinguished young lecturer) [slides]

New problems and techniques in stochastic optimization (Utah 2013, PKU 2014) [slides]

Stochastic Combinatorial Optimization via Poisson Approximation. (STOC Palo Alto 13)[Slides]

Uncertainty in Stochastic Optimization (MSRA Beijing 13, CAS Beijing 13, [Slides], WAIM summer school, Macau, 2014 [slides])

Maximizing Expected Utility for Stochastic Combinatorial Optimization Problems [slides] (FOCS Palm Springs 11, ISMP Berlin 12, Tsinghua-MIT-CUHK workshop HK 12)

Handling Uncertainty in Data Management [slides] (HotDB, Beijing 2012)

Generalized Machine Activation Problems. (San Francisco, SODA11).[Slides]

Ranking Continuous Probabilistic Datasets. (Singapore, VLDB10).[Slides]

New Models and Algorithms for Throughput Maximization in Broadcast Scheduling. [Slides](Liverpool, WAOA10).

When LP is the Cure for Your Matching Woes: Improved Bounds for Stochastic Matchings. (Liverpool, ESA10, Aarhus 2012).[Slides]

On Computing Compression Trees for Data Collection in Wireless Sensor Networks.[Slides] (San Diego, INFOCOM10)

A unified approach to ranking in probabilistic databases (Lyon, VLDB09) [slides slides-long]

Consensus answers in probabilistic databases (Providence, PODS09)

Minimizing communication cost in distributed multi-query processing. (Shanghai, ICDE09)

More Efficient Algorithms and Analyses for Unequal Letter Cost Prefix-Free Coding. (Sendai, ISAAC07)

Introdution to prize of stability  (Fudan, 2007)

Densest k-Subgraph Approximation on Interval Graphs, Chordal Graphs and Planar Graphs [slides](HKUST, 2007)

Core Stability of simple flow game (Fudan, 2007)

Approximating maximum simple sharing problem (Kolkata, ISAAC06)

Multicommodity and multilevel facility location (Hong Kong, AAIM06)

Seminar on Graph Theory and Algorithms (Fudan 2006) [lecture 1: tree and extensions] [lecture 2: matching and extensions] [lecture 3: coloring and extensions]

A Beginner in Parameterized Complexity (Fudan 2006)

Approximating spanning trees with inner nodes cost.(Dalian, PDCAT05)

Triangle partition problem (Fudan 2005)

Interval packing problem & Multicommodity demand flow in a line (Fudan 2005)

Network Motifs: Simple Building Blocks of Complex Network (Fudan 2005)