Search Results for author: Chi Wang

Found 28 papers, 10 papers with code

Mining Robust Default Configurations for Resource-constrained AutoML

no code implementations20 Feb 2022 Moe Kayali, Chi Wang

Automatic machine learning (AutoML) is a key enabler of the mass deployment of the next generation of machine learning systems.

AutoML

Bounding the Last Mile: Efficient Learned String Indexing

no code implementations29 Nov 2021 Benjamin Spector, Andreas Kipf, Kapil Vaidya, Chi Wang, Umar Farooq Minhas, Tim Kraska

RSS achieves this by using the minimal string prefix to sufficiently distinguish the data unlike most learned approaches which index the entire string.

Fair AutoML

no code implementations11 Nov 2021 Qingyun Wu, Chi Wang

(1) Comparing to traditional AutoML systems, this system incorporates fairness assessment and unfairness mitigation organically, which makes it possible to quantify fairness of the machine learning models tried and mitigate their unfairness when necessary.

AutoML Fairness

Geometry Attention Transformer with Position-aware LSTMs for Image Captioning

1 code implementation1 Oct 2021 Chi Wang, Yulin Shen, Luping Ji

In recent years, transformer structures have been widely applied in image captioning with impressive performance.

Image Captioning

An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models

1 code implementation ACL 2021 Xueqing Liu, Chi Wang

We find that using the same time budget, HPO often fails to outperform grid search due to two reasons: insufficient time budget and overfitting.

Hyperparameter Optimization

ChaCha for Online AutoML

1 code implementation9 Jun 2021 Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi

We propose the ChaCha (Champion-Challengers) algorithm for making an online choice of hyperparameters in online learning settings.

AutoML online learning

Attention-guided Temporally Coherent Video Object Matting

1 code implementation24 May 2021 Yunke Zhang, Chi Wang, Miaomiao Cui, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Hujun Bao, QiXing Huang, Weiwei Xu

Experimental results show that our method can generate high-quality alpha mattes for various videos featuring appearance change, occlusion, and fast motion.

Image Matting Semantic Segmentation +3

DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation

no code implementations ICLR 2021 Minjia Zhang, Menghao Li, Chi Wang, Mingqin Li

Recently, the DL compiler, together with Learning to Compile has proven to be a powerful technique for optimizing deep learning models.

Decision Making

ECONOMIC HYPERPARAMETER OPTIMIZATION WITH BLENDED SEARCH STRATEGY

no code implementations ICLR 2021 Chi Wang, Qingyun Wu, Silu Huang, Amin Saied

We study the problem of using low cost to search for hyperparameter configurations in a large search space with heterogeneous evaluation cost and model quality.

Hyperparameter Optimization

AdaTune: Adaptive Tensor Program Compilation Made Efficient

no code implementations NeurIPS 2020 Menghao Li, Minjia Zhang, Chi Wang, Mingqin Li

Deep learning models are computationally intense, and implementations often have to be highly optimized by experts or hardware vendors to be usable in practice.

A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices

no code implementations NeurIPS 2020 Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, Jie Tang

Our result gives the first bound on the convergence rate of the co-occurrence matrix and the first sample complexity analysis in graph representation learning.

Graph Learning Graph Representation Learning

Faster Graph Embeddings via Coarsening

1 code implementation ICML 2020 Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang

As computing Schur complements is expensive, we give a nearly-linear time algorithm that generates a coarsened graph on the relevant vertices that provably matches the Schur complement in expectation in each iteration.

Link Prediction Node Classification

Frugal Optimization for Cost-related Hyperparameters

1 code implementation4 May 2020 Qingyun Wu, Chi Wang, Silu Huang

To address this problem, we develop a new cost-frugal HPO solution.

Hyperparameter Optimization

Qd-tree: Learning Data Layouts for Big Data Analytics

no code implementations22 Apr 2020 Zongheng Yang, Badrish Chandramouli, Chi Wang, Johannes Gehrke, Yi-Nan Li, Umar Farooq Minhas, Per-Åke Larson, Donald Kossmann, Rajeev Acharya

For a given workload, however, such techniques are unable to optimize for the important metric of the number of blocks accessed by a query.

TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network

2 code implementations26 Jan 2020 Jiaming Shen, Zhihong Shen, Chenyan Xiong, Chi Wang, Kuansan Wang, Jiawei Han

Taxonomies consist of machine-interpretable semantics and provide valuable knowledge for many web applications.

Product Recommendation

FLAML: A Fast and Lightweight AutoML Library

2 code implementations12 Nov 2019 Chi Wang, Qingyun Wu, Markus Weimer, Erkang Zhu

We study the problem of using low computational cost to automate the choices of learners and hyperparameters for an ad-hoc training dataset and error metric, by conducting trials of different configurations on the given training data.

Hyperparameter Optimization

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

1 code implementation26 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.

Network Embedding

ALEX: An Updatable Adaptive Learned Index

no code implementations21 May 2019 Jialin Ding, Umar Farooq Minhas, JIA YU, Chi Wang, Jaeyoung Do, Yi-Nan Li, Hantian Zhang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David Lomet, Tim Kraska

The original work by Kraska et al. shows that a learned index beats a B+Tree by a factor of up to three in search time and by an order of magnitude in memory footprint.

ABC: Efficient Selection of Machine Learning Configuration on Large Dataset

no code implementations8 Nov 2018 Silu Huang, Chi Wang, Bolin Ding, Surajit Chaudhuri

A machine learning configuration refers to a combination of preprocessor, learner, and hyperparameters.

Identifying Outlier Arms in Multi-Armed Bandit

no code implementations NeurIPS 2017 Honglei Zhuang, Chi Wang, Yifan Wang

Outlier detection is a powerful method to narrow down the attention to a few objects after the data for them are collected.

Outlier Detection

Identifying Semantically Deviating Outlier Documents

no code implementations EMNLP 2017 Honglei Zhuang, Chi Wang, Fangbo Tao, Lance Kaplan, Jiawei Han

A document outlier is a document that substantially deviates in semantics from the majority ones in a corpus.

Outlier Detection

Scalable Topical Phrase Mining from Text Corpora

no code implementations24 Jun 2014 Ahmed El-Kishky, Yanglei Song, Chi Wang, Clare Voss, Jiawei Han

Our solution combines a novel phrase mining framework to segment a document into single and multi-word phrases, and a new topic model that operates on the induced document partition.

Topic Models

Scalable and Robust Construction of Topical Hierarchies

no code implementations13 Mar 2014 Chi Wang, Xueqing Liu, Yanglei Song, Jiawei Han

Automated generation of high-quality topical hierarchies for a text collection is a dream problem in knowledge engineering with many valuable applications.

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