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Articles 1531 - 1560 of 7454
Full-Text Articles in Physical Sciences and Mathematics
Figcps: Effective Failure-Inducing Input Generation For Cyber-Physical Systems With Deep Reinforcement Learning, Shaohua Zhang, Shuang Liu, Jun Sun, Yuqi Chen, Wenzhi Huang, Jinyi Liu, Jian Liu, Jianye Hao
Figcps: Effective Failure-Inducing Input Generation For Cyber-Physical Systems With Deep Reinforcement Learning, Shaohua Zhang, Shuang Liu, Jun Sun, Yuqi Chen, Wenzhi Huang, Jinyi Liu, Jian Liu, Jianye Hao
Research Collection School Of Computing and Information Systems
Cyber-Physical Systems (CPSs) are composed of computational control logic and physical processes, that intertwine with each other. CPSs are widely used in various domains of daily life, including those safety-critical systems and infrastructures, such as medical monitoring, autonomous vehicles, and water treatment systems. It is thus critical to effectively test them. However, it is not easy to obtain test cases which can fail the CPS. In this work, we propose a failure-inducing input generation approach FIGCPS for CPS, which requires no knowledge of the CPS under test or any history logs of the CPS which are usually hard to obtain. …
Using Role Play To Develop An Empathetic Mindset In Executive Education, Anuradha Ravi, Kasun Gamlath, Siyan Hu, Archan Misra
Using Role Play To Develop An Empathetic Mindset In Executive Education, Anuradha Ravi, Kasun Gamlath, Siyan Hu, Archan Misra
Research Collection School Of Computing and Information Systems
We describe the practical development of a smart lighting control system, CS-Light, that uses a preexisting surveillance camera infrastructure as the sole sensing substrate. At a high level, the camera feeds are used to both (a) estimate the illuminance of individual, fine-grained (roughly 12m2) sub-regions, and (b) identify sub-regions that have non-transient human occupancy. Subsequently, these estimates are used to perform fine-grained (non-binary) power optimization of a set of LED luminaires, collectively minimizing energy consumption while assuring comfort to human occupants. The key to our approach is the ability to tackle the challenging problem of translating the luminance (pixel intensity) …
Representation Learning On Multi-Layered Heterogeneous Network, Delvin Ce Zhang, Hady W. Lauw
Representation Learning On Multi-Layered Heterogeneous Network, Delvin Ce Zhang, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Network data can often be represented in a multi-layered structure with rich semantics. One example is e-commerce data, containing user-user social network layer and item-item context layer, with cross-layer user-item interactions. Given the dual characters of homogeneity within each layer and heterogeneity across layers, we seek to learn node representations from such a multi-layered heterogeneous network while jointly preserving structural information and network semantics. In contrast, previous works on network embedding mainly focus on single-layered or homogeneous networks with one type of nodes and links. In this paper we propose intra- and cross-layer proximity concepts. Intra-layer proximity simulates propagation along …
Patchnet: Hierarchical Deep Learning-Based Stable Patch Identification For The Linux Kernel, Thong Hoang, Julia Lawall, Yuan Tian, Richard J. Oentaryo, David Lo
Patchnet: Hierarchical Deep Learning-Based Stable Patch Identification For The Linux Kernel, Thong Hoang, Julia Lawall, Yuan Tian, Richard J. Oentaryo, David Lo
Research Collection School Of Computing and Information Systems
Linux kernel stable versions serve the needs of users who value stability of the kernel over new features. The quality of such stable versions depends on the initiative of kernel developers and maintainers to propagate bug fixing patches to the stable versions. Thus, it is desirable to consider to what extent this process can be automated. A previous approach relies on words from commit messages and a small set of manually constructed code features. This approach, however, shows only moderate accuracy. In this paper, we investigate whether deep learning can provide a more accurate solution. We propose PatchNet, a hierarchical …
Artificial Intelligence As Augmenting Automation: Implications For Employment, F. Ted Tschang, Esteve Almirall
Artificial Intelligence As Augmenting Automation: Implications For Employment, F. Ted Tschang, Esteve Almirall
Research Collection Lee Kong Chian School Of Business
There has been great concern in recent years that artificial intelligence (AI) may cause widespread unemployment, but proponents say that AI augments existing jobs. Both of these positions have substance, but there is a need is to articulate the mechanisms by which AI may actually do both, and in the process, transform work and business organizations alike. We use economic studies showing past transformations automation wrought on the structure of employment and skills (such as the favouring of nonroutine skills) to articulate a ground for discussion. We then use case evidence of AI and automation to show how AI is …
Efficient Online-Friendly Two-Party Ecdsa Signature, Haiyang Xue, Ho Man Au, Xiang Xie, Hon Tsz Yuen, Handong Cui
Efficient Online-Friendly Two-Party Ecdsa Signature, Haiyang Xue, Ho Man Au, Xiang Xie, Hon Tsz Yuen, Handong Cui
Research Collection School Of Computing and Information Systems
Two-party ECDSA signatures have received much attention due to their widespread deployment in cryptocurrencies. Depending on whether or not the message is required, we could divide two-party signing into two different phases, namely, offline and online. Ideally, the online phase should be made as lightweight as possible. At the same time, the cost of the offline phase should remain similar to that of a normal signature generation. However, the existing two-party protocols of ECDSA are not optimal: either their online phase requires decryption of a ciphertext, or their offline phase needs at least two executions of multiplicative-to-additive conversion which dominates …
Expediting The Accuracy-Improving Process Of Svms For Class Imbalance Learning, Bin Cao, Yuqi Liu, Chenyu Hou, Jing Fan, Baihua Zheng, Jianwei Jin
Expediting The Accuracy-Improving Process Of Svms For Class Imbalance Learning, Bin Cao, Yuqi Liu, Chenyu Hou, Jing Fan, Baihua Zheng, Jianwei Jin
Research Collection School Of Computing and Information Systems
To improve the classification performance of support vector machines (SVMs) on imbalanced datasets, cost-sensitive learning methods have been proposed, e.g., DEC (Different Error Costs) and FSVM-CIL (Fuzzy SVM for Class Imbalance Learning). They relocate the hyperplane by adjusting the costs associated with misclassifying samples. However, the error costs are determined either empirically or by performing an exhaustive search in the parameter space. Both strategies can not guarantee effectiveness and efficiency simultaneously. In this paper, we propose ATEC, a solution that can efficiently find a preferable hyperplane by automatically tuning the error cost for between-class samples. ATEC distinguishes itself from all …
On A Multistage Discrete Stochastic Optimization Problem With Stochastic Constraints And Nested Sampling, Thuy Anh Ta, Tien Mai, Fabian Bastin, Pierre L'Ecuyer
On A Multistage Discrete Stochastic Optimization Problem With Stochastic Constraints And Nested Sampling, Thuy Anh Ta, Tien Mai, Fabian Bastin, Pierre L'Ecuyer
Research Collection School Of Computing and Information Systems
We consider a multistage stochastic discrete program in which constraints on any stage might involve expectations that cannot be computed easily and are approximated by simulation. We study a sample average approximation (SAA) approach that uses nested sampling, in which at each stage, a number of scenarios are examined and a number of simulation replications are performed for each scenario to estimate the next-stage constraints. This approach provides an approximate solution to the multistage problem. To establish the consistency of the SAA approach, we first consider a two-stage problem and show that in the second-stage problem, given a scenario, the …
Focus On Sustainable Cities: Urban Solutions Toward Desired Outcomes, M. Georgescu, M. Arabi, Winston T. L. Chow, E. Mack, K. C. Seto
Focus On Sustainable Cities: Urban Solutions Toward Desired Outcomes, M. Georgescu, M. Arabi, Winston T. L. Chow, E. Mack, K. C. Seto
Research Collection School of Social Sciences
Urbanization represents the single most impactful and long-lasting transformation of the Earth system since the dawn of civilization. Cities are simultaneously locations of innovation, social connectivity, and wealth, but they also create local-to-global environmental degradation and socioeconomic disparities. For example, food provision for cities has required significant land-use change and fertilizer input, has altered regional climate, biogeochemical cycles, and degraded marine and landscapes through biodiversity loss, algal blooms and fish kills. To maintain urban livelihoods and the provision of goods and services, cities require vast amounts of energy (e.g. to provide access to transport, cooling systems), which are massive producers …
Ai: Friend Or Foe? (And What Business Leaders Need To Know), Singapore Management University
Ai: Friend Or Foe? (And What Business Leaders Need To Know), Singapore Management University
Perspectives@SMU
Artificial intelligence presents significant opportunities for business – as well as not insignificant threats to humanity – and governance frameworks are urgently needed to create a fair and equitable future under AI
Investing For The Future, Saker Nusseibeh
Investing For The Future, Saker Nusseibeh
Perspectives@SMU
Even if you don’t believe in climate change, shifting consumer and governmental attitudes make businesses that prioritise sustainability more profitable
Sustainable Investment Across Generations, Darren Teo, Elaine Teo, Jansen Phee, Mitch Reznick, Reshma Lalvani Sujan, Ronil Sujan
Sustainable Investment Across Generations, Darren Teo, Elaine Teo, Jansen Phee, Mitch Reznick, Reshma Lalvani Sujan, Ronil Sujan
Perspectives@SMU
Children that follow in a successful company’s founder's footsteps are paying more attention to sustainability
Disambiguating Mentions Of Api Methods In Stack Overflow Via Type Scoping, Kien Luong, Ferdian Thung, David Lo
Disambiguating Mentions Of Api Methods In Stack Overflow Via Type Scoping, Kien Luong, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
Stack Overflow is one of the most popular venues for developers to find answers to their API-related questions. However, API mentions in informal text content of Stack Overflow are often ambiguous and thus it could be difficult to find the APIs and learn their usages. Disambiguating these API mentions is not trivial, as an API mention can match with names of APIs from different libraries or even the same one. In this paper, we propose an approach called DATYS to disambiguate API mentions in informal text content of Stack Overflow using type scoping. With type scoping, we consider API methods …
Holoboard: A Large-Format Immersive Teaching Board Based On Pseudo Holographics, Jiangtao Gong, Teng Han, Siling Guo, Jiannan Li, Siyu Zha, Liuxin Zhang, Feng Tian, Qianying Wang, Yong Rui
Holoboard: A Large-Format Immersive Teaching Board Based On Pseudo Holographics, Jiangtao Gong, Teng Han, Siling Guo, Jiannan Li, Siyu Zha, Liuxin Zhang, Feng Tian, Qianying Wang, Yong Rui
Research Collection School Of Computing and Information Systems
In this paper, we present HoloBoard, an interactive large-format pseduo-holographic display system for lecture based classes. With its unique properties of immersive visual display and transparent screen, we designed and implemented a rich set of novel interaction techniques like immersive presentation, role-play, and lecturing behind the scene that are potentially valuable for lecturing in class. We conducted a controlled experimental study to compare a HoloBoard class with a normal class through measuring students’ learning outcomes and three dimensions of engagement (i.e., behavioral, emotional, and cognitive engagement). We used pre-/post- knowledge tests and multimodal learning analytics to measure students’ learning outcomes …
A Large-Scale Benchmark For Food Image Segmentation, Xiongwei Wu, Xin Fu, Ying Liu, Ee-Peng Lim, Steven C. H. Hoi, Qianru Sun
A Large-Scale Benchmark For Food Image Segmentation, Xiongwei Wu, Xin Fu, Ying Liu, Ee-Peng Lim, Steven C. H. Hoi, Qianru Sun
Research Collection School Of Computing and Information Systems
Food image segmentation is a critical and indispensible task for developing health-related applications such as estimating food calories and nutrients. 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 …
Route Tapestries: Navigating 360° Virtual Tour Videos Using Slit-Scan Visualizations, Jiannan Li, Jiahe Lyu, Maurício Sousa, Ravin Balakrishnan, Anthony Tang, Tovi Grossman
Route Tapestries: Navigating 360° Virtual Tour Videos Using Slit-Scan Visualizations, Jiannan Li, Jiahe Lyu, Maurício Sousa, Ravin Balakrishnan, Anthony Tang, Tovi Grossman
Research Collection School Of Computing and Information Systems
An increasingly popular way of experiencing remote places is by viewing 360° virtual tour videos, which show the surrounding view while traveling through an environment. However, finding particular locations in these videos can be difficult because current interfaces rely on distorted frame previews for navigation. To alleviate this usability issue, we propose Route Tapestries, continuous orthographic-perspective projection of scenes along camera routes. We first introduce an algorithm for automatically constructing Route Tapestries from a 360° video, inspired by the slit-scan photography technique. We then present a desktop video player interface using a Route Tapestry timeline for navigation. An online evaluation …
Improving The Performance Of Transportation Networks: A Semi-Centralized Pricing Approach, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Liujiang Kang, Xuexi Zhang, Qilun Wu
Improving The Performance Of Transportation Networks: A Semi-Centralized Pricing Approach, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Liujiang Kang, Xuexi Zhang, Qilun Wu
Research Collection School Of Computing and Information Systems
Improving the performance of transportation network is a crucial task in traffic management. In this paper, we start with a cooperative routing problem, which aims to minimize the chance of road network breakdown. To address this problem, we propose a subgradient method, which can be naturally implemented as a semi-centralized pricing approach. Particularly, each road link adopts the pricing scheme to calculate and adjust the local toll regularly, while the vehicles update their routes to minimize the toll costs by exploiting the global toll information. To prevent the potential oscillation brought by the subgradient method, we introduce a heavy-ball method …
Revocable Policy-Based Chameleon Hash, Shengmin Xu, Jianting Ning, Jinhua Ma, Guowen Xu, Jiaming Yuan, Robert H. Deng
Revocable Policy-Based Chameleon Hash, Shengmin Xu, Jianting Ning, Jinhua Ma, Guowen Xu, Jiaming Yuan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Policy-based chameleon hash (PCH) is a cryptographic building block which finds increasing practical applications. Given a message and an access policy, for any chameleon hash generated by a PCH scheme, a chameleon trapdoor holder whose rewriting privileges satisfy the access policy can amend the underlying message without affecting the hash value. In practice, it is necessary to revoke the rewriting privileges of a trapdoor holder due to various reasons, such as change of positions, compromise of credentials, or malicious behaviours. In this paper, we introduce the notion of revocable PCH (RPCH) and formally define its security. We instantiate a concrete …
Visionary Caption: Improving The Accessibility Of Presentation Slides Through Highlighting Visualization, Carmen Ji Yan Yip, Jie Mi Chong, Sin Yee Kwek, Yong Wang, Kotaro Hara
Visionary Caption: Improving The Accessibility Of Presentation Slides Through Highlighting Visualization, Carmen Ji Yan Yip, Jie Mi Chong, Sin Yee Kwek, Yong Wang, Kotaro Hara
Research Collection School Of Computing and Information Systems
Presentation slides are widely used in occasions such as academic talks and business meetings. Captions placed on slides support deaf and hard of hearing (DHH) people to understand spoken contents, but simultaneously comprehending and associating visual contents on slides and caption text could be challenging. In this paper, we design and develop a visualization technique to highlight and associate chart on a slide and numerical data in caption. We first conduct a small formative study with people with and without hearing impairments to assess the value of the visualization technique using a lo-fidelity video prototype. We then develop Visionary Caption, …
Conquer: Contextual Query-Aware Ranking For Video Corpus Moment Retrieval, Zhijian Hou, Chong-Wah Ngo, W. K. Chan
Conquer: Contextual Query-Aware Ranking For Video Corpus Moment Retrieval, Zhijian Hou, Chong-Wah Ngo, W. K. Chan
Research Collection School Of Computing and Information Systems
This paper tackles a recently proposed Video Corpus Moment Retrieval task. This task is essential because advanced video retrieval applications should enable users to retrieve a precise moment from a large video corpus. We propose a novel CONtextual QUery-awarE Ranking (CONQUER) model for effective moment localization and ranking. CONQUER explores query context for multi-modal fusion and representation learning in two different steps. The first step derives fusion weights for the adaptive combination of multi-modal video content. The second step performs bi-directional attention to tightly couple video and query as a single joint representation for moment localization. As query context is …
Interactive Probing Of Multivariate Time Series Prediction Models: A Case Of Freight Rate Analysis, Haonan Xu, Haotian Li, Yong Wang
Interactive Probing Of Multivariate Time Series Prediction Models: A Case Of Freight Rate Analysis, Haonan Xu, Haotian Li, Yong Wang
Research Collection School Of Computing and Information Systems
We present an interactive probing tool to create, modify and analyze what-if scenarios for multivariate time series models. The solution is applied to freight trading, where analysts can carry out sensitivity analysis on freight rates by changing demand and supply-related econometric variables and observing their resultant effects on freight indexes. We utilize various visualization techniques to enable intuitive scenario creation, alteration, and comprehension of time series inputs and model predictions. Our tool proved to be useful to the industry practitioners, demonstrated by a case study where freight traders are given hypothetical market scenarios and successfully generated quantitative freight index projection …
Visilence: An Interactive Visualization Tool For Error Resilience Analysis, Shaolun Ruan, Yong Wang, Qiang Guan
Visilence: An Interactive Visualization Tool For Error Resilience Analysis, Shaolun Ruan, Yong Wang, Qiang Guan
Research Collection School Of Computing and Information Systems
Soft errors have become one of the major concerns for HPC applications, as those errors can result in seriously corrupted outcomes, such as silent data corruptions (SDCs). Prior studies on error resilience have studied the robustness of HPC applications. However, it is still difficult for program developers to identify potential vulnerability to soft errors. In this paper, we present Visilence, a novel visualization tool to visually analyze error vulnerability based on the control-flow graph generated from HPC applications. Visilence efficiently visualizes the affected program states under injected errors and presents the visual analysis of the most vulnerable parts of an …
Cloudnplay: Resource Optimization For A Cloud-Native Gaming System, Angelus Wibowo, Nguyen Binh Duong Ta
Cloudnplay: Resource Optimization For A Cloud-Native Gaming System, Angelus Wibowo, Nguyen Binh Duong Ta
Research Collection School Of Computing and Information Systems
Cloud gaming enables people playing graphically intensive games from their less powerful, or even outdated computing devices. It is challenging to realize cloud gaming as it requires minimal latency in server-side processing, rendering and streaming, which are expensive in terms of resource requirements, e.g., powerful GPU servers. Commercial gaming providers, e.g., Google Stadia, Amazon Luna, etc., hardly disclose any information on how they optimize gaming performance and cloud cost. In this work, we aim to investigate resource cost optimization for such cloud gaming systems. In contrast to previous work which have been focusing more on theoretical approaches, we deliver a …
A First Look At Accessibility Issues In Popular Github Projects, Tingting Bi, Xin Xia, David Lo, Aldeida Aleti
A First Look At Accessibility Issues In Popular Github Projects, Tingting Bi, Xin Xia, David Lo, Aldeida Aleti
Research Collection School Of Computing and Information Systems
Accessibility design elements allow people to access software products and services independent of their different abilities. However, accessibility is challenging to handle and whether accessibility is widely considered in software projects is unclear. In this work, we aim to understand if accessibility is a prevalent consideration in practice, what accessibility issues are discussed in GitHub projects, what potential reasons cause accessibility issues, and what solutions (e.g., tools and standards) are applied for addressing accessibility issues. In this work, we collect 11,820 accessibility issues and their threads discussed by developers in popular GitHub projects. We manually analyzed and grouped the collected …
Online Learning: A Comprehensive Survey, Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao
Online Learning: A Comprehensive Survey, Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao
Research Collection School Of Computing and Information Systems
Online learning represents a family of machine learning methods, where a learner attempts to tackle some predictive (or any type of decision-making) task by learning from a sequence of data instances one by one at each time. The goal of online learning is to maximize the accuracy/correctness for the sequence of predictions/decisions made by the online learner given the knowledge of correct answers to previous prediction/learning tasks and possibly additional information. This is in contrast to traditional batch or offline machine learning methods that are often designed to learn a model from the entire training data set at once. Online …
Solarslam: Battery-Free Loop Closure For Indoor Localisation, Bo Wei, Weitao Xu, Chengwen Luo, Guillaume Zoppi, Dong Ma, Sen Wang
Solarslam: Battery-Free Loop Closure For Indoor Localisation, Bo Wei, Weitao Xu, Chengwen Luo, Guillaume Zoppi, Dong Ma, Sen Wang
Research Collection School Of Computing and Information Systems
In this paper, we propose SolarSLAM, a batteryfree loop closure method for indoor localisation. Inertial Measurement Unit (IMU) based indoor localisation method has been widely used due to its ubiquity in mobile devices, such as mobile phones, smartwatches and wearable bands. However, it suffers from the unavoidable long term drift. To mitigate the localisation error, many loop closure solutions have been proposed using sophisticated sensors, such as cameras, laser, etc. Despite achieving high-precision localisation performance, these sensors consume a huge amount of energy. Different from those solutions, the proposed SolarSLAM takes advantage of an energy harvesting solar cell as a …
Burst-Induced Multi-Armed Bandit For Learning Recommendation, Rodrigo Alves, Antoine Ledent, Marius Kloft
Burst-Induced Multi-Armed Bandit For Learning Recommendation, Rodrigo Alves, Antoine Ledent, Marius Kloft
Research Collection School Of Computing and Information Systems
In this paper, we introduce a non-stationary and context-free Multi-Armed Bandit (MAB) problem and a novel algorithm (which we refer to as BMAB) to solve it. The problem is context-free in the sense that no side information about users or items is needed. We work in a continuous-time setting where each timestamp corresponds to a visit by a user and a corresponding decision regarding recommendation. The main novelty is that we model the reward distribution as a consequence of variations in the intensity of the activity, and thereby we assist the exploration/exploitation dilemma by exploring the temporal dynamics of the …
Bv-Person: A Large-Scale Dataset For Bird-View Person Re-Identification, Cheng Yan, Guansong Pang, Lei Wang, Jile Jiao, Xuetao Feng, Chunhua Shen, Jingjing Li
Bv-Person: A Large-Scale Dataset For Bird-View Person Re-Identification, Cheng Yan, Guansong Pang, Lei Wang, Jile Jiao, Xuetao Feng, Chunhua Shen, Jingjing Li
Research Collection School Of Computing and Information Systems
Person Re-IDentification (ReID) aims at re-identifying persons from non-overlapping cameras. Existing person ReID studies focus on horizontal-view ReID tasks, in which the person images are captured by the cameras from a (nearly) horizontal view. In this work we introduce a new ReID task, bird-view person ReID, which aims at searching for a person in a gallery of horizontal-view images with the query images taken from a bird's-eye view, i.e., an elevated view of an object from above. The task is important because there are a large number of video surveillance cameras capturing persons from such an elevated view at public …
Using Role Play To Develop An Empathetic Mindset In Executive Education, Siu Loon Hoe, Tamsin Greulich-Smith
Using Role Play To Develop An Empathetic Mindset In Executive Education, Siu Loon Hoe, Tamsin Greulich-Smith
Research Collection School Of Computing and Information Systems
The purpose of this article is to discuss the importance of a role play activity as part of an experiential instructional strategy to develop an empathetic mindset among professionals, managers, and executives (PMEs) attending an executive education program in change management. This article provides an approach and process for management educators and facilitators of executive education programs to introduce and teach role play for the busy executives to learn about empathy. Role play is a useful teaching method that helps adult learners understand the importance of seeing things from another person’s point of view especially within a short period of …
Direct Differentiable Augmentation Search, Aoming Liu, Zehao Huang, Zhiwu Huang, Huang, Naiyan Wang
Direct Differentiable Augmentation Search, Aoming Liu, Zehao Huang, Zhiwu Huang, Huang, Naiyan Wang
Research Collection School Of Computing and Information Systems
Data augmentation has been an indispensable tool to improve the performance of deep neural networks, however the augmentation can hardly transfer among different tasks and datasets. Consequently, a recent trend is to adopt AutoML technique to learn proper augmentation policy without extensive hand-crafted tuning. In this paper, we propose an efficient differentiable search algorithm called Direct Differentiable Augmentation Search (DDAS). It exploits meta-learning with one-step gradient update and continuous relaxation to the expected training loss for efficient search. Our DDAS can achieve efficient augmentation search without relying on approximations such as Gumbel-Softmax or second order gradient approximation. To further reduce …