Search Results for author: Steven C. H. Hoi

Found 97 papers, 54 papers with code

Activity Regularization for Continual Learning

no code implementations ICLR 2019 Quang H. Pham, Steven C. H. Hoi

While deep neural networks have achieved remarkable successes, they suffer the well-known catastrophic forgetting issue when switching from existing tasks to tackle a new one.

Continual Learning Multi-Task Learning

RAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair

no code implementations12 Sep 2023 Weishi Wang, Yue Wang, Shafiq Joty, Steven C. H. Hoi

Automatic program repair (APR) is crucial to reduce manual debugging efforts for developers and improve software reliability.

Language Modelling Program Repair +1

PyRCA: A Library for Metric-based Root Cause Analysis

1 code implementation20 Jun 2023 Chenghao Liu, Wenzhuo Yang, Himanshu Mittal, Manpreet Singh, Doyen Sahoo, Steven C. H. Hoi

We introduce PyRCA, an open-source Python machine learning library of Root Cause Analysis (RCA) for Artificial Intelligence for IT Operations (AIOps).

Causal Discovery graph construction

OTW: Optimal Transport Warping for Time Series

no code implementations1 Jun 2023 Fabian Latorre, Chenghao Liu, Doyen Sahoo, Steven C. H. Hoi

Dynamic Time Warping (DTW) has become the pragmatic choice for measuring distance between time series.

Clustering Dynamic Time Warping +1

CodeTF: One-stop Transformer Library for State-of-the-art Code LLM

1 code implementation31 May 2023 Nghi D. Q. Bui, Hung Le, Yue Wang, Junnan Li, Akhilesh Deepak Gotmare, Steven C. H. Hoi

In this paper, we present CodeTF, an open-source Transformer-based library for state-of-the-art Code LLMs and code intelligence.

BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing

1 code implementation NeurIPS 2023 Dongxu Li, Junnan Li, Steven C. H. Hoi

Then we design a subject representation learning task which enables a diffusion model to leverage such visual representation and generates new subject renditions.

Representation Learning

CodeT5+: Open Code Large Language Models for Code Understanding and Generation

1 code implementation13 May 2023 Yue Wang, Hung Le, Akhilesh Deepak Gotmare, Nghi D. Q. Bui, Junnan Li, Steven C. H. Hoi

To address these limitations, we propose ``CodeT5+'', a family of encoder-decoder LLMs for code in which component modules can be flexibly combined to suit a wide range of downstream code tasks.

Arithmetic Reasoning Code Completion +4

AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges

no code implementations10 Apr 2023 Qian Cheng, Doyen Sahoo, Amrita Saha, Wenzhuo Yang, Chenghao Liu, Gerald Woo, Manpreet Singh, Silvio Saverese, Steven C. H. Hoi

There are a wide variety of problems to address, and multiple use-cases, where AI capabilities can be leveraged to enhance operational efficiency.

From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language Models

2 code implementations21 Dec 2022 Jiaxian Guo, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Boyang Li, DaCheng Tao, Steven C. H. Hoi

To address this issue, we propose \emph{Img2Prompt}, a plug-and-play module that provides the prompts that can bridge the aforementioned modality and task disconnections, so that LLMs can perform zero-shot VQA tasks without end-to-end training.

Question Answering Visual Question Answering

Learning Label Modular Prompts for Text Classification in the Wild

1 code implementation30 Nov 2022 Hailin Chen, Amrita Saha, Shafiq Joty, Steven C. H. Hoi

Machine learning models usually assume i. i. d data during training and testing, but data and tasks in real world often change over time.

text-classification Text Classification

LAVIS: A Library for Language-Vision Intelligence

1 code implementation15 Sep 2022 Dongxu Li, Junnan Li, Hung Le, Guangsen Wang, Silvio Savarese, Steven C. H. Hoi

We introduce LAVIS, an open-source deep learning library for LAnguage-VISion research and applications.

Benchmarking Image Captioning +8

Continual Learning, Fast and Slow

1 code implementation6 Sep 2022 Quang Pham, Chenghao Liu, Steven C. H. Hoi

Motivated by this theory, we propose \emph{DualNets} (for Dual Networks), a general continual learning framework comprising a fast learning system for supervised learning of pattern-separated representation from specific tasks and a slow learning system for representation learning of task-agnostic general representation via Self-Supervised Learning (SSL).

Continual Learning Hippocampus +2

Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval

no code implementations29 Jul 2022 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

When we do online paired data augmentation, we first generate augmented text through random token replacement, then pass the augmented text into the latent space alignment module to output the latent codes, which are finally fed to StyleGAN2 to generate the augmented images.

Cross-Modal Retrieval Data Augmentation +3

3D Cartoon Face Generation with Controllable Expressions from a Single GAN Image

no code implementations29 Jul 2022 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

To this end, we discover the semantic meanings of StyleGAN latent space, such that we are able to produce face images of various expressions, poses, and lighting by controlling the latent codes.

Face Generation Face Model

CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning

2 code implementations5 Jul 2022 Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven C. H. Hoi

To address the limitations, we propose "CodeRL", a new framework for program synthesis tasks through pretrained LMs and deep reinforcement learning (RL).

Code Generation Program Synthesis +2

A Causal Approach to Detecting Multivariate Time-series Anomalies and Root Causes

no code implementations30 Jun 2022 Wenzhuo Yang, Kun Zhang, Steven C. H. Hoi

In light of the modularity property of causal systems (the causal processes to generate different variables are irrelevant modules), the original problem is divided into a series of separate, simpler, and low-dimensional anomaly detection problems so that where an anomaly happens (root causes) can be directly identified.

Anomaly Detection Time Series +1

Multimodal Dialogue State Tracking

1 code implementation NAACL 2022 Hung Le, Nancy F. Chen, Steven C. H. Hoi

Specifically, we introduce a novel dialogue state tracking task to track the information of visual objects that are mentioned in video-grounded dialogues.

Dialogue State Tracking Video Understanding

Masked Unsupervised Self-training for Label-free Image Classification

1 code implementation7 Jun 2022 Junnan Li, Silvio Savarese, Steven C. H. Hoi

We demonstrate the efficacy of MUST on a variety of downstream tasks, where it improves upon CLIP by a large margin.

Image Classification Representation Learning +1

OmniXAI: A Library for Explainable AI

2 code implementations1 Jun 2022 Wenzhuo Yang, Hung Le, Tanmay Laud, Silvio Savarese, Steven C. H. Hoi

We introduce OmniXAI (short for Omni eXplainable AI), an open-source Python library of eXplainable AI (XAI), which offers omni-way explainable AI capabilities and various interpretable machine learning techniques to address the pain points of understanding and interpreting the decisions made by machine learning (ML) in practice.

counterfactual Counterfactual Explanation +5

MACE: An Efficient Model-Agnostic Framework for Counterfactual Explanation

1 code implementation31 May 2022 Wenzhuo Yang, Jia Li, Caiming Xiong, Steven C. H. Hoi

Counterfactual explanation is an important Explainable AI technique to explain machine learning predictions.

BIG-bench Machine Learning counterfactual +1

Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding

1 code implementation23 May 2022 Rishabh Bhardwaj, Amrita Saha, Steven C. H. Hoi, Soujanya Poria

VIP particularly focuses on two aspects -- contextual prompts that learns input-specific contextualization of the soft prompt tokens through a small-scale sentence encoder and quantized prompts that maps the contextualized prompts to a set of learnable codebook vectors through a Vector quantization network.

Natural Language Understanding NER +2

Mining Root Cause Knowledge from Cloud Service Incident Investigations for AIOps

no code implementations21 Apr 2022 Amrita Saha, Steven C. H. Hoi

ICA forms the backbone of a simple-yet-effective Retrieval based RCA for new incidents, through an Information Retrieval system to search and rank past incidents and detect likely root causes from them, given the incident symptom.

Information Retrieval Management +1

Learning Fast and Slow for Online Time Series Forecasting

1 code implementation23 Feb 2022 Quang Pham, Chenghao Liu, Doyen Sahoo, Steven C. H. Hoi

The fast adaptation capability of deep neural networks in non-stationary environments is critical for online time series forecasting.

Time Series Time Series Forecasting

Align and Prompt: Video-and-Language Pre-training with Entity Prompts

1 code implementation CVPR 2022 Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, Steven C. H. Hoi

To achieve this, we first introduce an entity prompter module, which is trained with VTC to produce the similarity between a video crop and text prompts instantiated with entity names.

Entity Alignment Retrieval +3

Node-wise Localization of Graph Neural Networks

1 code implementation27 Oct 2021 Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi

Ideally, how a node receives its neighborhood information should be a function of its local context, to diverge from the global GNN model shared by all nodes.

Representation Learning

Improving Tail-Class Representation with Centroid Contrastive Learning

no code implementations19 Oct 2021 Anthony Meng Huat Tiong, Junnan Li, Guosheng Lin, Boyang Li, Caiming Xiong, Steven C. H. Hoi

ICCL interpolates two images from a class-agnostic sampler and a class-aware sampler, and trains the model such that the representation of the interpolative image can be used to retrieve the centroids for both source classes.

Contrastive Learning Image Classification +2

Cascaded Fast and Slow Models for Efficient Semantic Code Search

no code implementations15 Oct 2021 Akhilesh Deepak Gotmare, Junnan Li, Shafiq Joty, Steven C. H. Hoi

The goal of natural language semantic code search is to retrieve a semantically relevant code snippet from a fixed set of candidates using a natural language query.

Code Search Re-Ranking +1

Learning Structural Representations for Recipe Generation and Food Retrieval

no code implementations4 Oct 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Our approach brings together several novel ideas in a systematic framework: (1) exploiting an unsupervised learning approach to obtain the sentence-level tree structure labels before training; (2) generating trees of target recipes from images with the supervision of tree structure labels learned from (1); and (3) integrating the learned tree structures into the recipe generation and food cross-modal retrieval procedure.

Cross-Modal Retrieval Image Captioning +2

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

5 code implementations EMNLP 2021 Yue Wang, Weishi Wang, Shafiq Joty, Steven C. H. Hoi

We present CodeT5, a unified pre-trained encoder-decoder Transformer model that better leverages the code semantics conveyed from the developer-assigned identifiers.

Clone Detection Code Summarization +4

Cross-Modal Graph with Meta Concepts for Video Captioning

1 code implementation14 Aug 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Video captioning targets interpreting the complex visual contents as text descriptions, which requires the model to fully understand video scenes including objects and their interactions.

object-detection Object Detection +1

Cycle-Consistent Inverse GAN for Text-to-Image Synthesis

no code implementations3 Aug 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

In this paper, we propose a novel unified framework of Cycle-consistent Inverse GAN (CI-GAN) for both text-to-image generation and text-guided image manipulation tasks.

Image Manipulation

$C^3$: Compositional Counterfactual Contrastive Learning for Video-grounded Dialogues

no code implementations16 Jun 2021 Hung Le, Nancy F. Chen, Steven C. H. Hoi

Video-grounded dialogue systems aim to integrate video understanding and dialogue understanding to generate responses that are relevant to both the dialogue and video context.

Contrastive Learning counterfactual +2

A Large-Scale Benchmark for Food Image Segmentation

2 code implementations12 May 2021 Xiongwei Wu, Xin Fu, Ying Liu, Ee-Peng Lim, Steven C. H. Hoi, Qianru Sun

Existing food image segmentation models are underperforming due to two reasons: (1) there is a lack of high quality food image datasets with fine-grained ingredient labels and pixel-wise location masks -- the existing datasets either carry coarse ingredient labels or are small in size; and (2) the complex appearance of food makes it difficult to localize and recognize ingredients in food images, e. g., the ingredients may overlap one another in the same image, and the identical ingredient may appear distinctly in different food images.

Ranked #3 on Semantic Segmentation on FoodSeg103 (using extra training data)

Image Segmentation Segmentation +1

VGNMN: Video-grounded Neural Module Network to Video-Grounded Language Tasks

no code implementations16 Apr 2021 Hung Le, Nancy F. Chen, Steven C. H. Hoi

Neural module networks (NMN) have achieved success in image-grounded tasks such as Visual Question Answering (VQA) on synthetic images.

Information Retrieval Question Answering +2

Weakly Supervised Neuro-Symbolic Module Networks for Numerical Reasoning

no code implementations28 Jan 2021 Amrita Saha, Shafiq Joty, Steven C. H. Hoi

Neural Module Networks (NMNs) have been quite successful in incorporating explicit reasoning as learnable modules in various question answering tasks, including the most generic form of numerical reasoning over text in Machine Reading Comprehension (MRC).

Dependency Parsing Language Modelling +2

Weakly-Supervised Multi-Face 3D Reconstruction

1 code implementation6 Jan 2021 Jialiang Zhang, Lixiang Lin, Jianke Zhu, Steven C. H. Hoi

3D face reconstruction plays a very important role in many real-world multimedia applications, including digital entertainment, social media, affection analysis, and person identification.

3D Face Reconstruction 3D Reconstruction +3

Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling

no code implementations22 Oct 2020 Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi

Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising.

Transfer Learning

BiST: Bi-directional Spatio-Temporal Reasoning for Video-Grounded Dialogues

1 code implementation EMNLP 2020 Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi

Video-grounded dialogues are very challenging due to (i) the complexity of videos which contain both spatial and temporal variations, and (ii) the complexity of user utterances which query different segments and/or different objects in videos over multiple dialogue turns.

Response Selection for Multi-Party Conversations withDynamic Topic Tracking

no code implementations15 Oct 2020 Weishi Wang§, Shafiq Joty§, Steven C. H. Hoi

While participants in a multi-party multi-turn conversation simultaneously engage in multiple conversation topics, existing response selection methods are developed mainly focusing on a two-party single-conversation scenario.

Disentanglement Multi-Task Learning +1

Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading

1 code implementation EMNLP 2020 Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu

Based on the learned EDU and entailment representations, we either reply to the user our final decision "yes/no/irrelevant" of the initial question, or generate a follow-up question to inquiry more information.

Decision Making Discourse Segmentation +3

MoPro: Webly Supervised Learning with Momentum Prototypes

2 code implementations ICLR 2021 Junnan Li, Caiming Xiong, Steven C. H. Hoi

We propose momentum prototypes (MoPro), a simple contrastive learning method that achieves online label noise correction, out-of-distribution sample removal, and representation learning.

Contrastive Learning Image Classification +2

Structure-Aware Generation Network for Recipe Generation from Images

1 code implementation ECCV 2020 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

We investigate an open research task of generating cooking instructions based on only food images and ingredients, which is similar to the image captioning task.

Image Captioning Recipe Generation

Bilevel Continual Learning

1 code implementation30 Jul 2020 Quang Pham, Doyen Sahoo, Chenghao Liu, Steven C. H. Hoi

Continual learning aims to learn continuously from a stream of tasks and data in an online-learning fashion, being capable of exploiting what was learned previously to improve current and future tasks while still being able to perform well on the previous tasks.

Bilevel Optimization Continual Learning +2

Decomposing Generation Networks with Structure Prediction for Recipe Generation

no code implementations27 Jul 2020 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Recipe generation from food images and ingredients is a challenging task, which requires the interpretation of the information from another modality.

Image Captioning Recipe Generation

Multi-label Thoracic Disease Image Classification with Cross-Attention Networks

no code implementations21 Jul 2020 Congbo Ma, Hu Wang, Steven C. H. Hoi

Automated disease classification of radiology images has been emerging as a promising technique to support clinical diagnosis and treatment planning.

Classification General Classification +2

Adaptive Task Sampling for Meta-Learning

no code implementations ECCV 2020 Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi

Meta-learning methods have been extensively studied and applied in computer vision, especially for few-shot classification tasks.

Classification General Classification +1

Theory-Inspired Path-Regularized Differential Network Architecture Search

1 code implementation NeurIPS 2020 Pan Zhou, Caiming Xiong, Richard Socher, Steven C. H. Hoi

Then we propose a theory-inspired path-regularized DARTS that consists of two key modules: (i) a differential group-structured sparse binary gate introduced for each operation to avoid unfair competition among operations, and (ii) a path-depth-wise regularization used to incite search exploration for deep architectures that often converge slower than shallow ones as shown in our theory and are not well explored during the search.

Image Classification

Video-Grounded Dialogues with Pretrained Generation Language Models

no code implementations ACL 2020 Hung Le, Steven C. H. Hoi

Pre-trained language models have shown remarkable success in improving various downstream NLP tasks due to their ability to capture dependencies in textual data and generate natural responses.

EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading

1 code implementation26 May 2020 Yifan Gao, Chien-Sheng Wu, Shafiq Joty, Caiming Xiong, Richard Socher, Irwin King, Michael R. Lyu, Steven C. H. Hoi

The goal of conversational machine reading is to answer user questions given a knowledge base text which may require asking clarification questions.

Decision Making Reading Comprehension

Prototypical Contrastive Learning of Unsupervised Representations

2 code implementations ICLR 2021 Junnan Li, Pan Zhou, Caiming Xiong, Steven C. H. Hoi

This paper presents Prototypical Contrastive Learning (PCL), an unsupervised representation learning method that addresses the fundamental limitations of instance-wise contrastive learning.

Clustering Contrastive Learning +4

UniConv: A Unified Conversational Neural Architecture for Multi-domain Task-oriented Dialogues

1 code implementation EMNLP 2020 Hung Le, Doyen Sahoo, Chenghao Liu, Nancy F. Chen, Steven C. H. Hoi

Building an end-to-end conversational agent for multi-domain task-oriented dialogues has been an open challenge for two main reasons.

Dialogue State Tracking

VD-BERT: A Unified Vision and Dialog Transformer with BERT

1 code implementation EMNLP 2020 Yue Wang, Shafiq Joty, Michael R. Lyu, Irwin King, Caiming Xiong, Steven C. H. Hoi

By contrast, in this work, we propose VD-BERT, a simple yet effective framework of unified vision-dialog Transformer that leverages the pretrained BERT language models for Visual Dialog tasks.

Answer Generation Visual Dialog

Learning Video Object Segmentation from Unlabeled Videos

1 code implementation CVPR 2020 Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David Crandall, Steven C. H. Hoi

We propose a new method for video object segmentation (VOS) that addresses object pattern learning from unlabeled videos, unlike most existing methods which rely heavily on extensive annotated data.

Representation Learning Segmentation +5

Cross-Modal Food Retrieval: Learning a Joint Embedding of Food Images and Recipes with Semantic Consistency and Attention Mechanism

no code implementations9 Mar 2020 Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi

Food retrieval is an important task to perform analysis of food-related information, where we are interested in retrieving relevant information about the queried food item such as ingredients, cooking instructions, etc.

Cross-Modal Retrieval Retrieval

Tree-structured Attention with Hierarchical Accumulation

no code implementations ICLR 2020 Xuan-Phi Nguyen, Shafiq Joty, Steven C. H. Hoi, Richard Socher

Incorporating hierarchical structures like constituency trees has been shown to be effective for various natural language processing (NLP) tasks.

text-classification Text Classification +1

Non-Autoregressive Dialog State Tracking

1 code implementation ICLR 2020 Hung Le, Richard Socher, Steven C. H. Hoi

Recent efforts in Dialogue State Tracking (DST) for task-oriented dialogues have progressed toward open-vocabulary or generation-based approaches where the models can generate slot value candidates from the dialogue history itself.

dialog state tracking Dialogue State Tracking +2

Deep Learning for Person Re-identification: A Survey and Outlook

5 code implementations13 Jan 2020 Mang Ye, Jianbing Shen, Gaojie Lin, Tao Xiang, Ling Shao, Steven C. H. Hoi

The widely studied closed-world setting is usually applied under various research-oriented assumptions, and has achieved inspiring success using deep learning techniques on a number of datasets.

Cross-Modal Person Re-Identification Metric Learning +2

Detecting Cyberattacks in Industrial Control Systems Using Online Learning Algorithms

no code implementations8 Dec 2019 Guangxia Lia, Yulong Shena, Peilin Zhaob, Xiao Lu, Jia Liu, Yangyang Liu, Steven C. H. Hoi

Similar to other information systems, a significant threat to industrial control systems is the attack from cyberspace---the offensive maneuvers launched by "anonymous" in the digital world that target computer-based assets with the goal of compromising a system's functions or probing for information.

Continuous Control Intrusion Detection

Attribute-aware Pedestrian Detection in a Crowd

1 code implementation21 Oct 2019 Jialiang Zhang, Lixiang Lin, Yang Li, Yun-chen Chen, Jianke Zhu, Yao Hu, Steven C. H. Hoi

To tackle this critical problem, we propose an attribute-aware pedestrian detector to explicitly model people's semantic attributes in a high-level feature detection fashion.

Pedestrian Detection

Meta-RCNN: Meta Learning for Few-Shot Object Detection

no code implementations25 Sep 2019 Xiongwei Wu, Doyen Sahoo, Steven C. H. Hoi

Specifically, Meta-RCNN learns an object detector in an episodic learning paradigm on the (meta) training data.

Few-Shot Object Detection Meta-Learning +2

Recent Advances in Deep Learning for Object Detection

1 code implementation10 Aug 2019 Xiongwei Wu, Doyen Sahoo, Steven C. H. Hoi

Object detection is a fundamental visual recognition problem in computer vision and has been widely studied in the past decades.

Image Classification object-detection +1

Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems

1 code implementation ACL 2019 Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi

Developing Video-Grounded Dialogue Systems (VGDS), where a dialogue is conducted based on visual and audio aspects of a given video, is significantly more challenging than traditional image or text-grounded dialogue systems because (1) feature space of videos span across multiple picture frames, making it difficult to obtain semantic information; and (2) a dialogue agent must perceive and process information from different modalities (audio, video, caption, etc.)

Dialogue State Tracking Response Generation

Compositional Coding for Collaborative Filtering

1 code implementation9 May 2019 Chenghao Liu, Tao Lu, Xin Wang, Zhiyong Cheng, Jianling Sun, Steven C. H. Hoi

However, CF with binary codes naturally suffers from low accuracy due to limited representation capability in each bit, which impedes it from modeling complex structure of the data.

Collaborative Filtering Recommendation Systems

Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images

2 code implementations CVPR 2019 Hao Wang, Doyen Sahoo, Chenghao Liu, Ee-Peng Lim, Steven C. H. Hoi

Food computing is playing an increasingly important role in human daily life, and has found tremendous applications in guiding human behavior towards smart food consumption and healthy lifestyle.

Cross-Modal Retrieval Nutrition +2

Meta-Learning with Domain Adaptation for Few-Shot Learning under Domain Shift

no code implementations ICLR 2019 Doyen Sahoo, Hung Le, Chenghao Liu, Steven C. H. Hoi

Most existing work assumes that both training and test tasks are drawn from the same distribution, and a large amount of labeled data is available in the training tasks.

Domain Adaptation Few-Shot Learning +1

Deep Learning for Image Super-resolution: A Survey

5 code implementations16 Feb 2019 Zhihao Wang, Jian Chen, Steven C. H. Hoi

Image Super-Resolution (SR) is an important class of image processing techniques to enhance the resolution of images and videos in computer vision.

Image Super-Resolution

Robust Graph Learning from Noisy Data

1 code implementation17 Dec 2018 Zhao Kang, Haiqi Pan, Steven C. H. Hoi, Zenglin Xu

The proposed model is able to boost the performance of data clustering, semisupervised classification, and data recovery significantly, primarily due to two key factors: 1) enhanced low-rank recovery by exploiting the graph smoothness assumption, 2) improved graph construction by exploiting clean data recovered by robust PCA.

Clustering General Classification +7

Adaptive Cost-sensitive Online Classification

no code implementations6 Apr 2018 Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang

Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i) weighted sum of sensitivity and specificity; (ii) weighted misclassification cost.

Anomaly Detection Classification +2

URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection

3 code implementations9 Feb 2018 Hung Le, Quang Pham, Doyen Sahoo, Steven C. H. Hoi

This approach allows the model to capture several types of semantic information, which was not possible by the existing models.

BIG-bench Machine Learning Feature Engineering +1

Online Learning: A Comprehensive Survey

no code implementations8 Feb 2018 Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao

Online learning represents an important family of machine learning algorithms, in which a learner attempts to resolve an online prediction (or any type of decision-making) task by learning a model/hypothesis from a sequence of data instances one at a time.

BIG-bench Machine Learning Decision Making

Robust Estimation of Similarity Transformation for Visual Object Tracking

2 code implementations14 Dec 2017 Yang Li, Jianke Zhu, Steven C. H. Hoi, Wenjie Song, Zhefeng Wang, Hantang Liu

In order to efficiently search in such a large 4-DoF space in real-time, we formulate the problem into two 2-DoF sub-problems and apply an efficient Block Coordinates Descent solver to optimize the estimation result.

Visual Object Tracking

Feature Agglomeration Networks for Single Stage Face Detection

no code implementations3 Dec 2017 Jialiang Zhang, Xiongwei Wu, Jianke Zhu, Steven C. H. Hoi

In this paper, we propose a novel simple yet effective framework of "Feature Agglomeration Networks" (FANet) to build a new single stage face detector, which not only achieves state-of-the-art performance but also runs efficiently.

Face Detection

Online Deep Learning: Learning Deep Neural Networks on the Fly

4 code implementations10 Nov 2017 Doyen Sahoo, Quang Pham, Jing Lu, Steven C. H. Hoi

Deep Neural Networks (DNNs) are typically trained by backpropagation in a batch learning setting, which requires the entire training data to be made available prior to the learning task.

Projection-free Distributed Online Learning in Networks

no code implementations ICML 2017 Wenpeng Zhang, Peilin Zhao, Wenwu Zhu, Steven C. H. Hoi, Tong Zhang

The conditional gradient algorithm has regained a surge of research interest in recent years due to its high efficiency in handling large-scale machine learning problems.

Face Detection using Deep Learning: An Improved Faster RCNN Approach

no code implementations28 Jan 2017 Xudong Sun, Pengcheng Wu, Steven C. H. Hoi

In this report, we present a new face detection scheme using deep learning and achieve the state-of-the-art detection performance on the well-known FDDB face detetion benchmark evaluation.

Face Detection

Malicious URL Detection using Machine Learning: A Survey

1 code implementation25 Jan 2017 Doyen Sahoo, Chenghao Liu, Steven C. H. Hoi

This article aims to provide a comprehensive survey and a structural understanding of Malicious URL Detection techniques using machine learning.

BIG-bench Machine Learning

SOL: A Library for Scalable Online Learning Algorithms

1 code implementation28 Oct 2016 Yue Wu, Steven C. H. Hoi, Chenghao Liu, Jing Lu, Doyen Sahoo, Nenghai Yu

SOL is an open-source library for scalable online learning algorithms, and is particularly suitable for learning with high-dimensional data.

BIG-bench Machine Learning General Classification +1

Online Bayesian Collaborative Topic Regression

no code implementations28 May 2016 Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun

In this paper, we propose a novel scheme of Online Bayesian Collaborative Topic Regression (OBCTR) which is efficient and scalable for learning from data streams.

Recommendation Systems regression

Scalable Image Retrieval by Sparse Product Quantization

no code implementations15 Mar 2016 Qingqun Ning, Jianke Zhu, Zhiyuan Zhong, Steven C. H. Hoi, Chun Chen

Unlike the existing approaches, in this paper, we propose a novel approach called Sparse Product Quantization (SPQ) to encoding the high-dimensional feature vectors into sparse representation.

Content-Based Image Retrieval Quantization +1

Adaptive Subgradient Methods for Online AUC Maximization

no code implementations1 Feb 2016 Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong

Despite their encouraging results reported, the existing online AUC maximization algorithms often adopt simple online gradient descent approaches that fail to exploit the geometrical knowledge of the data observed during the online learning process, and thus could suffer from relatively larger regret.

Budget Online Multiple Kernel Learning

no code implementations16 Nov 2015 Jing Lu, Steven C. H. Hoi, Doyen Sahoo, Peilin Zhao

To overcome this drawback, we present a novel framework of Budget Online Multiple Kernel Learning (BOMKL) and propose a new Sparse Passive Aggressive learning to perform effective budget online learning.

General Classification

LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks

no code implementations8 Nov 2015 Steven C. H. Hoi, Xiongwei Wu, Hantang Liu, Yue Wu, Huiqiong Wang, Hui Xue, Qiang Wu

In this paper, we introduce "LOGO-Net", a large-scale logo image database for logo detection and brand recognition from real-world product images.

Logo Recognition object-detection +1

A Framework of Sparse Online Learning and Its Applications

no code implementations25 Jul 2015 Dayong Wang, Pengcheng Wu, Peilin Zhao, Steven C. H. Hoi

Unlike some existing online data stream classification techniques that are often based on first-order online learning, we propose a framework of Sparse Online Classification (SOC) for data stream classification, which includes some state-of-the-art first-order sparse online learning algorithms as special cases and allows us to derive a new effective second-order online learning algorithm for data stream classification.

Anomaly Detection Classification +1

Reliable Patch Trackers: Robust Visual Tracking by Exploiting Reliable Patches

no code implementations CVPR 2015 Yang Li, Jianke Zhu, Steven C. H. Hoi

Most modern trackers typically employ a bounding box given in the first frame to track visual objects, where their tracking results are often sensitive to the initialization.

Clustering Visual Tracking

Large-scale Online Feature Selection for Ultra-high Dimensional Sparse Data

no code implementations27 Sep 2014 Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu

However, unlike many second-order learning methods that often suffer from extra high computational cost, we devise a novel smart algorithm for second-order online feature selection using a MaxHeap-based approach, which is not only more effective than the existing first-order approaches, but also significantly more efficient and scalable for large-scale feature selection with ultra-high dimensional sparse data, as validated from our extensive experiments.

feature selection Vocal Bursts Intensity Prediction

Online Portfolio Selection: A Survey

2 code implementations10 Dec 2012 Bin Li, Steven C. H. Hoi

This article aims to provide a timely and comprehensive survey for both machine learning and data mining researchers in academia and quantitative portfolio managers in the financial industry to help them understand the state-of-the-art and facilitate their research and practical applications.

BIG-bench Machine Learning Meta-Learning

PAMR: Passive aggressive mean reversion strategy for portfolio selection

1 code implementation Machine Learning 2012 Bin Li, Peilin Zhao, Steven C. H. Hoi

This article proposes a novel online portfolio selection strategy named “Passive Aggressive Mean Reversion” (PAMR).

CORN: Correlation-driven Non parametric Learning Approach for Portfolio Selection

1 code implementation ACM Transactions on Intelligent Systems and Technology. 2 2011 Bin Li, Steven C. H. Hoi, Vivekanand GOPALKRISHNAN

Machine learning techniques have been adopted to select portfolios from financial markets in some emerging intelligent business applications.

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