b'Chi Wang'

research

∙ 08/16/2023

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework

This technical report presents AutoGen, a new framework that enables dev...

0 Qingyun Wu, et al. ∙

research

∙ 06/02/2023

An Empirical Study on Challenging Math Problem Solving with GPT-4

Employing Large Language Models (LLMs) to address mathematical problems ...

0 Yiran Wu, et al. ∙

research

∙ 05/28/2023

HyperTime: Hyperparameter Optimization for Combating Temporal Distribution Shifts

In this work, we propose a hyperparameter optimization method named Hype...

0 Shaokun Zhang, et al. ∙

research

∙ 03/08/2023

Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference

Large Language Models (LLMs) like GPT-3 have sparked significant interes...

0 Chi Wang, et al. ∙

research

∙ 08/04/2022

ACE: Adaptive Constraint-aware Early Stopping in Hyperparameter Optimization

Deploying machine learning models requires high model quality and needs ...

0 Yi-Wei Chen, et al. ∙

research

∙ 06/03/2022

Multivariate Sparse Group Lasso Joint Model for Radiogenomics Data

Radiogenomics is an emerging field in cancer research that combines medi...

0 Tiantian Zeng, et al. ∙

research

∙ 02/20/2022

Mining Robust Default Configurations for Resource-constrained AutoML

Automatic machine learning (AutoML) is a key enabler of the mass deploym...

0 Moe Kayali, et al. ∙

research

∙ 11/29/2021

Bounding the Last Mile: Efficient Learned String Indexing

We introduce the RadixStringSpline (RSS) learned index structure for eff...

0 Benjamin Spector, et al. ∙

research

∙ 11/11/2021

Fair AutoML

We present an end-to-end automated machine learning system to find machi...

10 Qingyun Wu, et al. ∙

research

∙ 10/29/2021

Estimating the Distribution of Ratio of Paired Event Times in Phase II Oncology Trials

With the rapid development of new anti-cancer agents which are cytostati...

0 Li Chen, et al. ∙

research

∙ 10/25/2021

Weighted Mean Difference Statistics for Paired Data in Presence of Missing Values

Missing data is a common issue in many biomedical studies. Under a paire...

0 Yuntong Li, et al. ∙

research

∙ 10/01/2021

Geometry Attention Transformer with Position-aware LSTMs for Image Captioning

In recent years, transformer structures have been widely applied in imag...

0 Chi Wang, et al. ∙

research

∙ 08/05/2021

Q-error Bounds of Random Uniform Sampling for Cardinality Estimation

Random uniform sampling has been studied in various statistical tasks bu...

0 Beibin Li, et al. ∙

research

∙ 06/17/2021

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

The performance of fine-tuning pre-trained language models largely depen...

0 Xueqing Liu, et al. ∙

research

∙ 06/09/2021

ChaCha for Online AutoML

We propose the ChaCha (Champion-Challengers) algorithm for making an onl...

0 Qingyun Wu, et al. ∙

research

∙ 02/04/2021

Active Boundary Loss for Semantic Segmentation

This paper proposes a novel active boundary loss for semantic segmentati...

34 Chi Wang, et al. ∙

research

∙ 10/01/2020

Understanding the hardness of approximate query processing with joins

We study the hardness of Approximate Query Processing (AQP) of various t...

0 Tianyu Liu, et al. ∙

research

∙ 08/11/2020

GEE-TGDR: A longitudinal feature selection algorithm and its application to lncRNA expression profiles for psoriasis patients treated with immune therapies

With the fast evolution of high-throughput technology, longitudinal gene...

0 Suyan Tian, et al. ∙

research

∙ 08/06/2020

Concentration Bounds for Co-occurrence Matrices of Markov Chains

Co-occurrence statistics for sequential data are common and important da...

0 Jiezhong Qiu, et al. ∙

research

∙ 07/06/2020

Faster Graph Embeddings via Coarsening

Graph embeddings are a ubiquitous tool for machine learning tasks, such ...

2 Matthew Fahrbach, et al. ∙

research

∙ 06/04/2020

Universal Graph Compression: Stochastic Block Models

Motivated by the prevalent data science applications of processing and m...

0 Alankrita Bhatt, et al. ∙

research

∙ 05/04/2020

Cost Effective Optimization for Cost-related Hyperparameters

The increasing demand for democratizing machine learning algorithms for ...

2 Qingyun Wu, et al. ∙

research

∙ 04/22/2020

Qd-tree: Learning Data Layouts for Big Data Analytics

Corporations today collect data at an unprecedented and accelerating sca...

0 Zongheng Yang, et al. ∙

research

∙ 11/12/2019

FLO: Fast and Lightweight Hyperparameter Optimization for AutoML

Integrating ML models in software is of growing interest. Building accur...

58 Chi Wang, et al. ∙

research

∙ 10/27/2019

Towards Extracting Highlights From Recorded Live Videos: An Implicit Crowdsourcing Approach

Live streaming platforms need to store a lot of recorded live videos on ...

0 Ruochen Jiang, et al. ∙

research

∙ 06/26/2019

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

We study the problem of large-scale network embedding, which aims to lea...

10 Jiezhong Qiu, et al. ∙

research

∙ 05/21/2019

ALEX: An Updatable Adaptive Learned Index

Recent work on "learned indexes" has revolutionized the way we look at t...

0 Jialin Ding, et al. ∙

research

∙ 11/08/2018

Efficient Identification of Approximate Best Configuration of Training in Large Datasets

A configuration of training refers to the combinations of feature engine...

0 Silu Huang, et al. ∙

research

∙ 03/13/2014

Scalable and Robust Construction of Topical Hierarchies

Automated generation of high-quality topical hierarchies for a text coll...

0 Chi Wang, et al. ∙

Chi Wang

Featured Co-authors