JavaScript as an Embedded DSL

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Type inference in the presence of first-class or "impredicative" second-order polymorphism a la System F has been an active research area for several decades, with original works dating back to the end of the 80s. Yet, until now many basic problems remain ...

The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

A metaprogrammer should be able to reason about the semantics of the generated code. Multi-stage programming introduced an elegant and powerful solution to this problem. It follows a semantically driven approach to code generation, where semantics are full ...

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

One major challenge in distributed learning is to efficiently learn for each client when the data across clients is heterogeneous or non iid (not independent or identically distributed). This provides a significant challenge as the data of the other client ...

Byzantine Reliable Broadcast (BRB) is a fundamental distributed computing primitive, with applications ranging from notifications to asynchronous payment systems. Motivated by practical consideration, we study Client-Server Byzantine Reliable Broadcast (CS ...

Formal verification of real-world software systems remains challenging for a number of reasons, including lack of automation, friction in specifying properties, and limited support for the diverse programming paradigms used in industry. In this thesis we m ...

Online services have become ubiquitous in technological society, the global demand for which has driven enterprises to construct gigantic datacenters that run their software. Such facilities have also recently become a substrate for third-party organizatio ...

In online data-intensive (OLDI) services, each client request typically executes on multiple servers in parallel; as a result, “system hiccups”, although rare within a single server, can interfere with many client requests and cause violations of service-l ...

Software engineering practices have been steadily moving towards higher-level programming languages and away from lower-level ones. High-level languages tend to greatly improve safety, productivity, and code maintainability because they handle various impl ...

Federated Learning (FL) is a machine learning setting where many devices collaboratively train a machine learning model while keeping the training data decentralized. In most of the current training schemes the central model is refined by averaging the par ...

The single-server multi-message private information retrieval with side information problem is studied for general cases. In this problem, K independent messages are stored at a single server. One user initially has M messages as side information and wants ...

A major theme of IT in the past decade has been the shift from on-premise hardware to cloud computing. Running a service in the public cloud is practical, because a large number of resources can be bought on-demand, but this shift comes with its own set of ...

In a modern data center (DC), a large majority of costs arise from energy consumption. The most popular technique used to mitigate this issue is virtualization and more precisely virtual machine (VM) consolidation. Although consolidation may increase serve ...

Improving the energy efficiency of data centers while guaranteeing Quality of Service (QoS), together with detecting performance variability of servers caused by either hardware or software failures, are two of the major challenges for efficient resource m ...

Programming languages are increasingly compiled to multiple runtimes, each featuring their own rich structures such as their object model. Furthermore, they need to interact with other languages targeting said runtimes. A language targeting only one runtim ...

We study the problem of single-server multi-message private information retrieval with side information. One user wants to recover N out of K independent messages which are stored at a single server. The user initially possesses a subset of M messages as s ...

This paper addresses the mean-field behavior of large-scale systems of parallel servers with a processor sharing service discipline when arrivals are Poisson and jobs have general service time distributions when an SQ(d) routing policy is used. Under this ...

A simple task of storing a database or transferring it to a different point via a communication channel turns far more complex as the size of the database grows large. Limited bandwidth available for transmission plays a central role in this predicament. I ...

JavaScript as an Embedded DSL

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When Subtyping Constraints Liberate A Novel Type Inference Approach for First-Class Polymorphism

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Scalable Metaprogramming in Scala 3

Privatized graph federated learning

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Oracular Byzantine Reliable Broadcast

Scaling Language Features for Program Verification

Hardware and Software Support for RPC-Centric Server Architecture

When to Hedge in Interactive Services

Type-Safe Metaprogramming and Compilation Techniques For Designing Efficient Systems in High-Level Languages

Ensemble Distillation for Robust Model Fusion in Federated Learning

Single-server Multi-message Private Information Retrieval with Side Information: the General Cases

Understanding and Mitigating Latency Variability of Latency-Critical Applications

Drowsy-DC: Data center power management system

MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers

Cross-Platform Language Design

Single-server Multi-message Private Information Retrieval with Side Information

The mean-field behavior of processor sharing systems with general job lengths under the SQ(d) policy

Caching and Distributed Storage : Models, Limits and Designs