Sublinear Approximation for Large-scale Data Science

出版物

表示方法:

- A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices
  
  Jiezhong Qiu, Chi Wang, Ben Liao, RIchard Peng, Jie Tang
  
  NeurIPS 2020 | December 2020
  
  Author's Version
- Understanding the Hardness of Approximate Query Processing with Joins
  
  Tianyu Liu, Chi Wang
  
  MSR-TR-2020-38 | October 2020
  
  Microsoft による投稿
  
  Publication
- Faster Graph Embeddings via Coarsening
  
  Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang
  
  International Conference on Machine Learning (ICML 2020) | July 2020
  
  Publication
- Fast Approximation of Empirical Entropy via Subsampling
  
  Chi Wang, Bailu Ding
  
  25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING | August 2019
  
  DOI Author's Version 動画プロジェクト
- NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
  
  Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang
  
  The Web Conference 2019 | May 2019
  
  Author's Version アクセスプロジェクトプロジェクト
- ABC: Efficient Selection of Machine Learning Configuration on Large Dataset
  
  Silu Huang, Chi Wang, Bolin Ding, Surajit Chaudhuri
  
  AAAI 2019 | January 2019
  
  Publication アクセスプロジェクト
- Efficient Attribute Recommendation with Probabilistic Guarantee
  
  Chi Wang, Kaushik Chakrabarti
  
  Proc. 2018 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining | July 2018
  
  Author's Version Publication
- Identifying Outlier Arms in Multi-Armed Bandit
  
  Honglei Zhuang, Chi Wang, Yifan Wang
  
  Advances in Neural Information Processing Systems 30 (NIPS 2017) | December 2017
  
  Author's Version Publication
- Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data
  
  Dominik Moritz, Danyel Fisher, Bolin Ding, Chi Wang
  
  Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems | May 2017
  
  Author's Version Publication 動画プロジェクト
- Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee
  
  Bolin Ding, Silu Huang, Surajit Chaudhuri, Kaushik Chakrabarti, Chi Wang
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2016) | July 2016
  
  Author's Version Publication

- A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices
  
  Jiezhong Qiu, Chi Wang, Ben Liao, RIchard Peng, Jie Tang
  
  NeurIPS 2020 | December 2020
  
  Author's Version
- Understanding the Hardness of Approximate Query Processing with Joins
  
  Tianyu Liu, Chi Wang
  
  MSR-TR-2020-38 | October 2020
  
  Microsoft による投稿
  
  Publication
- Faster Graph Embeddings via Coarsening
  
  Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang
  
  International Conference on Machine Learning (ICML 2020) | July 2020
  
  Publication
- Fast Approximation of Empirical Entropy via Subsampling
  
  Chi Wang, Bailu Ding
  
  25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING | August 2019
  
  DOI Author's Version 動画プロジェクト
- NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
  
  Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang
  
  The Web Conference 2019 | May 2019
  
  Author's Version アクセスプロジェクトプロジェクト
- Efficient Attribute Recommendation with Probabilistic Guarantee
  
  Chi Wang, Kaushik Chakrabarti
  
  Proc. 2018 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining | July 2018
  
  Author's Version Publication
- Identifying Outlier Arms in Multi-Armed Bandit
  
  Honglei Zhuang, Chi Wang, Yifan Wang
  
  Advances in Neural Information Processing Systems 30 (NIPS 2017) | December 2017
  
  Author's Version Publication
- Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data
  
  Dominik Moritz, Danyel Fisher, Bolin Ding, Chi Wang
  
  Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems | May 2017
  
  Author's Version Publication 動画プロジェクト
- Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee
  
  Bolin Ding, Silu Huang, Surajit Chaudhuri, Kaushik Chakrabarti, Chi Wang
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2016) | July 2016
  
  Author's Version Publication
- A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices
  
  Jiezhong Qiu, Chi Wang, Ben Liao, RIchard Peng, Jie Tang
  
  NeurIPS 2020 | December 2020
  
  Author's Version
- Understanding the Hardness of Approximate Query Processing with Joins
  
  Tianyu Liu, Chi Wang
  
  MSR-TR-2020-38 | October 2020
  
  Microsoft による投稿
  
  Publication
- A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices
  
  Jiezhong Qiu, Chi Wang, Ben Liao, RIchard Peng, Jie Tang
  
  NeurIPS 2020 | December 2020
  
  Author's Version
- Faster Graph Embeddings via Coarsening
  
  Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang
  
  International Conference on Machine Learning (ICML 2020) | July 2020
  
  Publication
- Fast Approximation of Empirical Entropy via Subsampling
  
  Chi Wang, Bailu Ding
  
  25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING | August 2019
  
  DOI Author's Version 動画プロジェクト
- NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
  
  Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang
  
  The Web Conference 2019 | May 2019
  
  Author's Version アクセスプロジェクトプロジェクト
- ABC: Efficient Selection of Machine Learning Configuration on Large Dataset
  
  Silu Huang, Chi Wang, Bolin Ding, Surajit Chaudhuri
  
  AAAI 2019 | January 2019
  
  Publication アクセスプロジェクト
- Identifying Outlier Arms in Multi-Armed Bandit
  
  Honglei Zhuang, Chi Wang, Yifan Wang
  
  Advances in Neural Information Processing Systems 30 (NIPS 2017) | December 2017
  
  Author's Version Publication
- Faster Graph Embeddings via Coarsening
  
  Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang
  
  International Conference on Machine Learning (ICML 2020) | July 2020
  
  Publication
- Fast Approximation of Empirical Entropy via Subsampling
  
  Chi Wang, Bailu Ding
  
  25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING | August 2019
  
  DOI Author's Version 動画プロジェクト
- Identifying Outlier Arms in Multi-Armed Bandit
  
  Honglei Zhuang, Chi Wang, Yifan Wang
  
  Advances in Neural Information Processing Systems 30 (NIPS 2017) | December 2017
  
  Author's Version Publication
- Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee
  
  Bolin Ding, Silu Huang, Surajit Chaudhuri, Kaushik Chakrabarti, Chi Wang
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2016) | July 2016
  
  Author's Version Publication
- Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data
  
  Dominik Moritz, Danyel Fisher, Bolin Ding, Chi Wang
  
  Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems | May 2017
  
  Author's Version Publication 動画プロジェクト

- Understanding the Hardness of Approximate Query Processing with Joins
  
  Tianyu Liu, Chi Wang
  
  MSR-TR-2020-38 | October 2020
  
  Microsoft による投稿
  
  Publication
- A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices
  
  Jiezhong Qiu, Chi Wang, Ben Liao, RIchard Peng, Jie Tang
  
  NeurIPS 2020 | December 2020
  
  Author's Version
- Faster Graph Embeddings via Coarsening
  
  Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang
  
  International Conference on Machine Learning (ICML 2020) | July 2020
  
  Publication
- Fast Approximation of Empirical Entropy via Subsampling
  
  Chi Wang, Bailu Ding
  
  25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING | August 2019
  
  DOI Author's Version 動画プロジェクト
- NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
  
  Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang
  
  The Web Conference 2019 | May 2019
  
  Author's Version アクセスプロジェクトプロジェクト
- ABC: Efficient Selection of Machine Learning Configuration on Large Dataset
  
  Silu Huang, Chi Wang, Bolin Ding, Surajit Chaudhuri
  
  AAAI 2019 | January 2019
  
  Publication アクセスプロジェクト
- Efficient Attribute Recommendation with Probabilistic Guarantee
  
  Chi Wang, Kaushik Chakrabarti
  
  Proc. 2018 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining | July 2018
  
  Author's Version Publication
- Identifying Outlier Arms in Multi-Armed Bandit
  
  Honglei Zhuang, Chi Wang, Yifan Wang
  
  Advances in Neural Information Processing Systems 30 (NIPS 2017) | December 2017
  
  Author's Version Publication
- Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data
  
  Dominik Moritz, Danyel Fisher, Bolin Ding, Chi Wang
  
  Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems | May 2017
  
  Author's Version Publication 動画プロジェクト
- Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee
  
  Bolin Ding, Silu Huang, Surajit Chaudhuri, Kaushik Chakrabarti, Chi Wang
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2016) | July 2016
  
  Author's Version Publication

Sublinear Approximation for Large-scale Data Science

出版物

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

Understanding the Hardness of Approximate Query Processing with Joins

Faster Graph Embeddings via Coarsening

Fast Approximation of Empirical Entropy via Subsampling

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

ABC: Efficient Selection of Machine Learning Configuration on Large Dataset

Efficient Attribute Recommendation with Probabilistic Guarantee

Identifying Outlier Arms in Multi-Armed Bandit

Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data

Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee

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

Understanding the Hardness of Approximate Query Processing with Joins

Faster Graph Embeddings via Coarsening

Fast Approximation of Empirical Entropy via Subsampling

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

Efficient Attribute Recommendation with Probabilistic Guarantee

Identifying Outlier Arms in Multi-Armed Bandit

Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data

Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee

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

Understanding the Hardness of Approximate Query Processing with Joins

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

Faster Graph Embeddings via Coarsening

Fast Approximation of Empirical Entropy via Subsampling

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

ABC: Efficient Selection of Machine Learning Configuration on Large Dataset

Identifying Outlier Arms in Multi-Armed Bandit

Faster Graph Embeddings via Coarsening

Fast Approximation of Empirical Entropy via Subsampling

Identifying Outlier Arms in Multi-Armed Bandit

Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee

Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data

Understanding the Hardness of Approximate Query Processing with Joins

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

Faster Graph Embeddings via Coarsening

Fast Approximation of Empirical Entropy via Subsampling

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

ABC: Efficient Selection of Machine Learning Configuration on Large Dataset

Efficient Attribute Recommendation with Probabilistic Guarantee

Identifying Outlier Arms in Multi-Armed Bandit

Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data

Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee