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LBCF: A Large-Scale Budget-Constrained Causal Forest Algorithm 22

LBCF: A Large-Scale Budget-Constrained Causal Forest Algorit...

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31st acm Web Conference (WWW)

作者： Ai, Meng Li, Biao Gong, Heyang Yu, Qingwei Xue, Shengjie Zhang, Yuan Zhang, Yunzhou Hang, Peng Kuaishou Inc Beijing Peoples R China Univ Sci & Technol China Hefei Peoples R China

ISBN: (纸本)9781450390965

Offering incentives (e.g., coupons at Amazon, discounts at Uber and video bonuses at Tiktok) to user is a common strategy used by online platforms to increase user engagement and platform revenue. Despite its proven effectiveness, these marketing incentives incur an inevitable cost and might result in a low ROI (Return on Investment) if not used properly. On the other hand, different users respond differently to these incentives, for instance, some users never buy certain products without coupons, while others do anyway. Thus, how to select the right amount of incentives (i.e. treatment) to each user under budget constraints is an important research problem with great practical implications. In this paper, we call such problem as a budget-constrained treatment selection (BTS) problem. The challenge is how to efficiently solve BTS problem on a Large-Scale dataset and achieve improved results over the existing techniques. We propose a novel tree-based treatment selection technique under budget constraints, called Large-Scale BudgetConstrained Causal Forest (LBCF) algorithm, which is also an efficient treatment selection algorithm suitable for modern distributed computing systems. A novel offline evaluation method is also proposed to overcome an intrinsic challenge in assessing solutions' performance for BTS problem in randomized control trials (RCT) data. We deploy our approach in a real-world scenario on a largescale video platform, where the platform gives away bonuses in order to increase users' campaign engagement duration. The simulation analysis, offline and online experiments all show that our method outperforms various tree-based state-of-the-art baselines 1. The proposed approach is currently serving over hundreds of millions of users on the platform and achieves one of the most tremendous improvements over these months.

关键词： Personalization Heterogeneous causal effects Constraint optimization Treatment Selection Distributed computing

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XCheck: Verifying Integrity of 3D Printed Patient-Specific Devices via computing Tomography 32

XCheck: Verifying Integrity of 3D Printed Patient-Specific D...

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32nd USENIX Security Symposium

作者： Yu, Zhiyuan Chang, Yuanhaur Zhai, Shixuan Deily, Nicholas Ju, Tao Wang, XiaoFeng Jammalamadaka, Uday Zhang, Ning Washington Univ St Louis MO USA Indiana Univ Bloomington IN USA Rice Univ Houston TX 77251 USA

ISBN: (纸本)9781939133373

3D printing is bringing revolutionary changes to the field of medicine, with applications ranging from hearing aids to regrowing organs. As our society increasingly relies on this technology to save lives, the security of these systems is a growing concern. However, existing defense approaches that leverage side channels may require domain knowledge from computer security to fully understand the impact of the attack. To bridge the gap, we propose XCheck, which leverages medical imaging to verify the integrity of the printed patient-specific device (PSD). XCheck follows a defense-in-depth approach and directly compares the computed tomography (CT) scan of the printed device to its original design. XCheck utilizes a voxel-based approach to build multiple layers of defense involving both 3D geometric verification and multivariate material analysis. To further enhance usability, XCheck also provides an adjustable visualization scheme that allows practitioners' inspection of the printed object with varying tolerance thresholds to meet the needs of different applications. We evaluated the system with 47 PSDs representing different medical applications to validate the efficacy.

关键词： Computerized tomography

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PreMatch: A Prediction-based Scheduler for Dataflow Asynchronous Processing on the computing Continuum 25

PreMatch: A Prediction-based Scheduler for Dataflow Asynchro...

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40th Annual acm Symposium on Applied computing, SAC 2025

作者： Mehran, Narges Najafabadi Samani, Zahra Afzal, Samira Prodan, Radu Pallas, Frank Dorfinger, Peter Faculty of Digital and Analytical Sciences Paris Lodron University of Salzburg Salzburg Austria Intelligent Connectivity Group Salzburg Research Forschungsgesellschaft MbH Salzburg Austria Distributed and Parallel Systems Group University of Innsbruck Tyrol Innsbruck Austria Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Overijssel Enschede Netherlands Institute of Information Technology Alpen-Adria-University of Klagenfurt Carinthia Klagenfurt Austria

ISBN: (纸本)9798400706295

The popularity of asynchronous data exchange patterns has recently increased, as evidenced by 23% of the communication between microservices in an Alibaba trace analysis. Such workloads necessitate methods for reducing dataflow processing and completion time by forecasting the future requirements of their microservices and (re-)scheduling them. Therefore, we investigate a prediction-based scheduling method of asynchronous dataflow processing applications by considering the stochastic changes due to dynamic user requirements. We present a microservice scaling and scheduling method named PreMatch combining a machine learning (ML) prediction strategy based on gradient boosting with ranking and game theory matching scheduling principles. Firstly, PreMatch predicts the number of microservice replicas, and then, the ranking method orders the microservice replicas and devices based on microservice and transmission times. Thereafter, the PreMatch schedules microservice replicas requiring dataflow processing on computing devices. Experimental analysis of the PreMatch method shows lower completion times on average 13% compared to a related prediction-based scheduling method. Copyright © 2025 held by the owner/author(s).

关键词： Data curation

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MSWiM 2021 - proceedings of the 24th International acm Conference on Modeling, analysis and Simulation of Wireless and Mobile systems

MSWiM 2021 - Proceedings of the 24th International ACM Confe...

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24th acm International Conference on Modelling, analysis, and Simulation of Wireless and Mobile systems, MSWiM 2021

ISBN: (纸本)9781450390774

The proceedings contain 29 papers. The topics discussed include: preventing failures of cooperative maneuvers among connected and automated vehicles;global energy optimization strategy based on delay constraints in edge computing environment;profit maximization for service placement and request assignment in edge computing via deep reinforcement learning;accelerating the simulation of wireless communication protocols using asynchronous parallelism;modeling and simulation of reconfigurable intelligent surfaces for hybrid aerial and ground-based vehicular communications;an energy-efficient smart space system using lora network with deadline and security constraints;a novel harvesting-aware RL-based opportunistic routing protocol for underwater sensor networks;and simple and efficient collision-free channel access in multi-hop wireless networks.

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Terrain Type Detection for Smart Equine Gait analysis systems Using Inertial Sensors and Machine Learning 19

Terrain Type Detection for Smart Equine Gait Analysis System...

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19th Annual International Conference on Distributed computing in Smart systems and the Internet of Things, DCOSS-IoT 2023

作者： Parmentier, Jeanne I.M. Braganca, Filipe M. Serra Hernlund, Elin Van Der Zwaag, Berend Jan Utrecht University Dept. of Clinical Sciences Utrecht Netherlands University of Twente Pervasive Systems Group Enschede Netherlands Swedish University of Agricultural Sciences Dept. of Anatomy Physiology and Biochemistry Uppsala Sweden

ISBN: (纸本)9798350346497

Lameness, limping due to pain, is a significant welfare issue for horses. Veterinarians typically evaluate horses on two terrain types (hard and soft, e.g., asphalt and sand) that are known to affect the observed degree of lameness based on the origin/location of the pain. In the past years, whole-body inertial measurement units (IMU)-based gait analysis systems were developed to support diagnostics and monitor locomotion changes over time. Movement direction and gait (walk, trot) are automatically labeled, resulting in smart and easy-to-use systems. However, terrain types are not detected, leading to information loss. In this work, we explored terrain classification tasks with equine IMU data and machine and deep learning. Using the data of 111 horses equipped with IMU sensors (withers, pelvis, front, and hind limbs), we compared different features-based (FT) and time-series-based (TS) classifiers (train-test ratio: 0.7-0.3). In order to reduce the computational costs of the future system, we also evaluated the performance (F1 score) of the classifiers with different sampling frequencies (10 to 200Hz) and different IMU combinations (body and limbs). Our Convolutional Neural Network models accurately classified terrain types with only one IMU placed on the front limb. Downsampling the signals led to similar results, thus enabling real-time applications. © 2023 IEEE.

关键词： Landforms

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Initial Study and Performance analysis of Vertical LoRa Using Drone in Forest Areas 9

Initial Study and Performance Analysis of Vertical LoRa Usin...

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9th International Conference on Computer, Control, Informatics and Its Applications: Digital Transformation Towards Sustainable Society for Post Covid-19 Recovery, IC3INA 2022

作者： Putra, Dimas Biwas Suwandi, Bondan Fitriani, Riski Herminawan, Fito Wibawa, Yoga Samudro, Moh Badan Riset Dan Inovasi Nasional Tangerang Selatan Banten Indonesia Badan Riset Dan Inovasi Nasional Tangerang Selatan Indonesia

ISBN: (纸本)9781450397919

Along with the development of drone technology, it is now possible to implement LoRa technology vertically, which can be used as a mobile LoRa repeater or tracker. We introduce the initial study and performance analysis of vertical LoRa communication using drones as forest repeater or trackers in monitoring systems. In addition, several test methods were also developed and carried out to determine whether using LoRa with drones vertically could increase the reception range of LoRa signals, particularly in forest areas considering vegetation density, signal propagation, multipath effect. From the results obtained in the experiments, the vertical LoRa system proved to have a better RSSI value than the horizontal LoRa system in forest areas. Using vertical LoRa at a distance of 100 meters shows a better RSSI value with a difference up to 16.24 dBm than the horizontal LoRa. In the forest with higher density, we got a variation of the RSSI measurement result of 4.67 to 4.73 dBm caused by the multipath effect. To conclude, the vertical LoRa using drones can improve the LoRa telecommunication coverage area and is possible to use as LoRa repeater or trackers. © 2022 acm.

关键词： Drones

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SIGMETRICS 2021 - Abstract proceedings of the 2021 acm SIGMETRICS / International Conference on measurement and Modeling of Computer systems

SIGMETRICS 2021 - Abstract Proceedings of the 2021 ACM SIGME...

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2021 acm SIGMETRICS / International Conference on measurement and Modeling of Computer systems, SIGMETRICS 2021

ISBN: (纸本)9781450380720

The proceedings contain 38 papers. The topics discussed include: federated bandit: a gossiping approach;statistically efficient, polynomial-time algorithms for combinatorial semi-bandits;information aggregation for constrained online control;online virtual machine allocation with lifetime and load predictions;zero queueing for multi-server jobs;the Gittins policy is nearly optimal in the M/G/k under extremely general conditions;where did my 256 GB go? a measurement analysis of storage consumption on smart mobile devices;a measurement study of Wechat mini-apps;a look behind the curtain: traffic classification in an increasingly encrypted web;achieving zero asymptotic queueing delay for parallel jobs;and on the asymptotic insensitivity of the supermarket model in processor sharing systems.

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Methodology for Evaluating the Potential of Disaggregated Memory systems 2

Methodology for Evaluating the Potential of Disaggregated Me...

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2nd IEEE/acm International Workshop on Resource Disaggregation in High-Performance computing, RESDIS 2022

作者： Ding, Nan Williams, Samuel Nam, Hai Ah Groves, Taylor Awan, Muaaz Gul Lindsey, LeAnn Daley, Christopher Selvitopi, Oguz Oliker, Leonid Wright, Nicholas Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

ISBN: (纸本)9781665488891

Tightly-coupled HPC systems have rigid memory allocation and can result in expensive memory resource underutilization. As novel memory and network technologies mature, disaggregated memory systems are becoming a promising solution for future HPC systems. It allows workloads to use the available memory of the entire system. In this paper, we propose a design framework to explore the disaggregated memory system design space. The framework incorporates memory capacity, network bandwidth, and local and remote memory access ratio, and provides an intuitive approach to guide machine configurations based on technology trends and workload characteristics. We apply our framework to analyze eleven workloads from five computational scenarios, including AI training, data analysis, genomics, protein, and traditional HPC. We demonstrate the ability of our methodology to understand the potential and pitfalls on a disaggregated memory system and motivate machine configurations. Our methodology shows that the 10 out of our 11 applications/workflows can leverage disaggregated memory without affecting performance. © 2022 IEEE.

关键词： Memory architecture

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HeteroBench: Multi-kernel Benchmarks for Heterogeneous systems 25

HeteroBench: Multi-kernel Benchmarks for Heterogeneous Syste...

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2025 International Conference on Performance Engineering-ICPE-Annual

作者： Tian, Hongzheng Mishra, Alok Chen, Zhiheng Enriquez, Rolando P. Hong Milojicic, Dejan Frachtenberg, Eitan Huang, Sitao Univ Calif Irvine Irvine CA 92717 USA Hewlett Packard Enterprise Milpitas CA 95035 USA

ISBN: (纸本)9798400710735

The end of Moore's Law and Dennard scaling has driven the proliferation of heterogeneous systems with accelerators, including CPUs, GPUs, and FPGAs, each with distinct architectures, compilers, and programming environments. GPUs excel at massively parallel processing for tasks like deep learning training and graphics rendering, while FPGAs offer hardware-level flexibility and energy efficiency for low-latency, high-throughput applications. In contrast, CPUs, while general-purpose, often fall short in high-parallelism or power-constrained applications. This architectural diversity makes it challenging to compare these accelerators effectively, leading to uncertainty in selecting optimal hardware and software tools for specific applications. To address this challenge, we introduce HeteroBench, a versatile benchmark suite for heterogeneous systems. HeteroBench allows users to evaluate multi-compute kernel applications across various accelerators, including CPUs, GPUs (fromNVIDIA, AMD, Intel), and FPGAs (AMD), supporting programming environments of Python, Numba-accelerated Python, serial C++, OpenMP (both CPUs and GPUs), OpenACC and CUDA for GPUs, and Vitis HLS for FPGAs. This setup enables users to assign kernels to suitable hardware platforms, ensuring comprehensive device comparisons. What makes HeteroBench unique is its vendor-agnostic, cross-platform approach, spanning diverse domains such as image processing, machine learning, numerical computation, and physical simulation, ensuring deeper insights for HPC optimization. Extensive testing across multiple systems provides practical reference points for HPC practitioners, simplifying hardware selection and performance tuning for both developers and end-users alike. This suite may assist to make more informed decision on AI/ML deployment and HPC development, making it an invaluable resource for advancing academic research and industrial applications.

关键词： Benchmark suite heterogeneous computing Python OpenMP CUDA OpenACC HLS High Performance computing CPU GPU FPGA

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Design and Characterization of the Output Network of a High-Current Buck Converter 46

Design and Characterization of the Output Network of a High-...

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46th ICT and Electronics Convention, MIPRO 2023

作者： Solaja, Kresimir Blecic, Raul Broznic, Andro Baric, Adrijan University of Zagreb Faculty of Electrical Engineering and Computing Department of Electronics Microelectronics Computer and Intelligent Systems Zagreb Croatia Rimac Technology d.o.o./Embedded Hardware Sveta Nedelja Croatia

ISBN: (纸本)9789532331042

A 10-A automotive buck converter is designed and realized on a four layer printed circuit board. The output network is designed in the electromagnetic solver to account for the trace and package parasitic elements. The output network of the converter is simulated in the SPICE solver. The converter is characterized in the time domain by the load transient measurements and in the frequency domain by the shunt measurement method. Three configurations of the output network are compared. The results in the frequency domain and the results of the SPICE simulations are correlated. © 2023 MIPRO Croatian Society.

关键词： Time domain analysis

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