Search Results for author: Yi-Ling Chen

Found 17 papers, 3 papers with code

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

no code implementations21 May 2023 ZiYi Yang, Mahmoud Khademi, Yichong Xu, Reid Pryzant, Yuwei Fang, Chenguang Zhu, Dongdong Chen, Yao Qian, Mei Gao, Yi-Ling Chen, Robert Gmyr, Naoyuki Kanda, Noel Codella, Bin Xiao, Yu Shi, Lu Yuan, Takuya Yoshioka, Michael Zeng, Xuedong Huang

The convergence of text, visual, and audio data is a key step towards human-like artificial intelligence, however the current Vision-Language-Speech landscape is dominated by encoder-only models which lack generative abilities.

Energy Efficiency Maximization in IRS-Aided Cell-Free Massive MIMO System

no code implementations24 Dec 2022 Si-Nian Jin, Dian-Wu Yue, Yi-Ling Chen, Qing Hu

In this paper, we consider an intelligent reflecting surface (IRS)-aided cell-free massive multiple-input multiple-output system, where the beamforming at access points and the phase shifts at IRSs are jointly optimized to maximize energy efficiency (EE).

Florence: A New Foundation Model for Computer Vision

1 code implementation22 Nov 2021 Lu Yuan, Dongdong Chen, Yi-Ling Chen, Noel Codella, Xiyang Dai, Jianfeng Gao, Houdong Hu, Xuedong Huang, Boxin Li, Chunyuan Li, Ce Liu, Mengchen Liu, Zicheng Liu, Yumao Lu, Yu Shi, Lijuan Wang, JianFeng Wang, Bin Xiao, Zhen Xiao, Jianwei Yang, Michael Zeng, Luowei Zhou, Pengchuan Zhang

Computer vision foundation models, which are trained on diverse, large-scale dataset and can be adapted to a wide range of downstream tasks, are critical for this mission to solve real-world computer vision applications.

Action Classification Action Recognition In Videos +12

Ubiquitous proximity to a critical state for collective neural activity in the CA1 region of freely moving mice

no code implementations26 Feb 2021 Yi-Ling Chen, Chun-Chung Chen, Yu-Ying Mei, Ning Zhou, Dongchuan Wu, Ting-Kuo Lee

By independently altering the coupling distribution and the network structure of the statistical model, the network structures are found to be vital to maintain the proximity to the critical state.

Hippocampus

Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication

no code implementations10 May 2020 Yang Liu, Michael Gordon, Juntao Wang, Michael Bishop, Yi-Ling Chen, Thomas Pfeiffer, Charles Twardy, Domenico Viganola

We will discuss opportunities and challenges of using these approaches to monitor and improve the credibility of research areas in Computer Science, AI, and ML.

Forecast Aggregation via Peer Prediction

no code implementations9 Oct 2019 Juntao Wang, Yang Liu, Yi-Ling Chen

In this paper, we study the problem of aggregating forecasts without having historical performance data.

Fair Classification and Social Welfare

no code implementations1 May 2019 Lily Hu, Yi-Ling Chen

By showing that these constraints often fail to translate into improved outcomes for these groups, we cast doubt on their effectiveness as a means to ensure justice.

Classification Fairness +1

Welfare and Distributional Impacts of Fair Classification

no code implementations3 Jul 2018 Lily Hu, Yi-Ling Chen

Current methodologies in machine learning analyze the effects of various statistical parity notions of fairness primarily in light of their impacts on predictive accuracy and vendor utility loss.

Classification Fairness +2

Surrogate Scoring Rules

no code implementations26 Feb 2018 Yang Liu, Juntao Wang, Yi-Ling Chen

We show that, with a single bit of information about the prior distribution of the random variables, SSR in a multi-task setting recover SPSR in expectation, as if having access to the ground truth.

Learning to Compose with Professional Photographs on the Web

1 code implementation1 Feb 2017 Yi-Ling Chen, Jan Klopp, Min Sun, Shao-Yi Chien, Kwan-Liu Ma

Photo composition is an important factor affecting the aesthetics in photography.

Image Cropping

Quantitative Analysis of Automatic Image Cropping Algorithms: A Dataset and Comparative Study

1 code implementation5 Jan 2017 Yi-Ling Chen, Tzu-Wei Huang, Kai-Han Chang, Yu-Chen Tsai, Hwann-Tzong Chen, Bing-Yu Chen

Automatic photo cropping is an important tool for improving visual quality of digital photos without resorting to tedious manual selection.

Image Cropping Learning-To-Rank +1

A Bandit Framework for Strategic Regression

no code implementations NeurIPS 2016 Yang Liu, Yi-Ling Chen

We propose a Strategic Regression-Upper Confidence Bound (SR-UCB) framework, an UCB-style index combined with a simple payment rule, where the index of a worker approximates the quality of his past contributions and is used by the learner to determine whether the worker receives future work.

regression

Eliciting Categorical Data for Optimal Aggregation

no code implementations NeurIPS 2016 Chien-Ju Ho, Rafael Frongillo, Yi-Ling Chen

Our model generalizes both categories and enables the joint exploration of optimal elicitation and aggregation.

Multiple-choice

Learning to Incentivize: Eliciting Effort via Output Agreement

no code implementations17 Apr 2016 Yang Liu, Yi-Ling Chen

In crowdsourcing when there is a lack of verification for contributed answers, output agreement mechanisms are often used to incentivize participants to provide truthful answers when the correct answer is hold by the majority.

Integrating Dashcam Views Through Inter-Video Mapping

no code implementations ICCV 2015 Hsin-I Chen, Yi-Ling Chen, Wei-Tse Lee, Fan Wang, Bing-Yu Chen

In this paper, an inter-video mapping approach is proposed to integrate video footages from two dashcams installed on a preceding and its following vehicle to provide the illusion that the driver of the following vehicle can see-through the preceding one.

Motion Estimation

Low-Cost Learning via Active Data Procurement

no code implementations20 Feb 2015 Jacob Abernethy, Yi-Ling Chen, Chien-Ju Ho, Bo Waggoner

Our results in a sense parallel classic sample complexity guarantees, but with the key resource being money rather than quantity of data: With a budget constraint $B$, we give robust risk (predictive error) bounds on the order of $1/\sqrt{B}$.

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