2 code implementations • 30 Jun 2022 • Eric R. Knorr, Baptiste Lemaire, Andrew Lim, Siqiang Luo, Huanchen Zhang, Stratos Idreos, Michael Mitzenmacher

We introduce Proteus, a novel self-designing approximate range filter, which configures itself based on sampled data in order to optimize its false positive rate (FPR) for a given space requirement.

1 code implementation • 6 Oct 2021 • Jingwen Li, Yining Ma, Ruize Gao, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang

To solve those problems, we propose a DRL method based on the attention mechanism with a vehicle selection decoder accounting for the heterogeneous fleet constraint and a node selection decoder accounting for the route construction, which learns to construct a solution by automatically selecting both a vehicle and a node for this vehicle at each step.

no code implementations • 6 Oct 2021 • Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang

In particular, the heterogeneous attention mechanism specifically prescribes attentions for each role of the nodes while taking into account the precedence constraint, i. e., the pickup node must precede the pairing delivery node.

no code implementations • ICCV 2021 • Xinke Li, Zhirui Chen, Yue Zhao, Zekun Tong, Yabang Zhao, Andrew Lim, Joey Tianyi Zhou

We present the backdoor attacks in 3D point cloud with a unified framework that exploits the unique properties of 3D data and networks.

1 code implementation • NeurIPS 2020 • Zekun Tong, Yuxuan Liang, Changsheng Sun, Xinke Li, David Rosenblum, Andrew Lim

Graph Convolutional Networks (GCNs) have shown promising results in modeling graph-structured data.

no code implementations • 22 Sep 2020 • Chongshou Li, Brenda Cheang, Zhixing Luo, Andrew Lim

The EFM model is significantly different from the original Factorization Machines (FM) from two-fold: (1) the attribute-level formulation for explanatory variables and (2) exponential formulation for the positive response variable.

no code implementations • 12 Aug 2020 • Jing Tang, Xueyan Tang, Andrew Lim, Kai Han, Chongshou Li, Junsong Yuan

Second, we enhance the modified greedy algorithm to derive a data-dependent upper bound on the optimum.

1 code implementation • 11 Aug 2020 • Xinke Li, Chongshou Li, Zekun Tong, Andrew Lim, Junsong Yuan, Yuwei Wu, Jing Tang, Raymond Huang

Based on it, we formulate a hierarchical learning problem for 3D point cloud segmentation and propose a measurement evaluating consistency across various hierarchies.

1 code implementation • 29 Apr 2020 • Zekun Tong, Yuxuan Liang, Changsheng Sun, David S. Rosenblum, Andrew Lim

Graph Convolutional Networks (GCNs) have been widely used due to their outstanding performance in processing graph-structured data.

2 code implementations • 14 Apr 2020 • Keke Huang, Jing Tang, Kai Han, Xiaokui Xiao, Wei Chen, Aixin Sun, Xueyan Tang, Andrew Lim

In this paper, we propose the first practical algorithm for the adaptive IM problem that could provide the worst-case approximation guarantee of $1-\mathrm{e}^{\rho_b(\varepsilon-1)}$, where $\rho_b=1-(1-1/b)^b$ and $\varepsilon \in (0, 1)$ is a user-specified parameter.

Social and Information Networks

1 code implementation • CVPR 2020 • Yue Zhao, Yuwei Wu, Caihua Chen, Andrew Lim

Armed with the Thompson Sampling, we develop a black-box attack with success rate over 95% on ModelNet40 data set.

1 code implementation • 23 Dec 2019 • Wen Song, Zhiguang Cao, Jie Zhang, Andrew Lim

In this paper, we propose a deep reinforcement learning based approach to automatically discover new variable ordering heuristics that are better adapted for a given class of CSP instances.

1 code implementation • 12 Dec 2019 • Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Andrew Lim

In this paper, we propose a deep reinforcement learning framework to learn the improvement heuristics for routing problems.

1 code implementation • 31 Jul 2016 • Pierre Thodoroff, Joelle Pineau, Andrew Lim

We present and evaluate the capacity of a deep neural network to learn robust features from EEG to automatically detect seizures.

no code implementations • 17 Sep 2014 • Hu Qin, Zizhen Zhang, Yubin Xie, Andrew Lim

Therefore, the shortest transit time between any vertex pair is affected by the length of the period and the departure time.

no code implementations • 23 Jan 2014 • Zizhen Zhang, Hu Qin, Xiaocong Liang, Andrew Lim

The talent scheduling problem is a simplified version of the real-world film shooting problem, which aims to determine a shooting sequence so as to minimize the total cost of the actors involved.

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