Publications by Rachid Guerraoui

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This paper presents type-based publish/subscribe, a new variant of the publish/subscribe paradigm. Producers publish message objects on a communication bus, and consumers subscribe to the bus by specifying the types of the objects they are interested in. Message objects are considered as first class citizens and are classified by their types, instead of arbitrarily fixed topics. By reusing the type scheme of the language to classify message objects, type-based publish/subscribe avoids any unnatural subscrip

The success of machine learning (ML) has been intimately linked with the availability of large amounts of data, typically collected from heterogeneous sources and processed on vast networks of computing devices (also called workers). Beyond accuracy, the u ...

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

The Transaction abstraction is arguably one of the most appealing middleware paradigms. It lies typically between the programmer of a concurrent or distributed application on the one hand, and the operating system with the underlying network on the other h ...

Transactional memory (TM) has shown potential to simplify the task of writing concurrent programs. Inspired by classical work on databases, formal definitions of the semantics of TM executions have been proposed. Many of these definitions assumed that acce ...

Smart thermostats are increasingly popular in homes and buildings as they improve occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills by automatically adjusting room temperature according to measurements of their bui ...

Shoals of small fishes can change their collective shape and form a specific pattern. They do so efficiently (in parallel) and without collision. In this paper, we study the analog problem of distributed pattern formation. A set of processes needs to move ...

Model checking transactional memories (TMs) is difficult because of the unbounded number, length, and delay of concurrent transactions, as well as the unbounded size of the memory. We show that, under certain conditions satisfied by most TMs we know of, th ...

The fair exchange problem is key to trading electronic items in systems of mutually untrusted parties. In modern variants of such systems, each party is equipped with a tamper proof security module. The security modules trust each other but can only communicate by exchanging messages through their host parties. These hosts are untrusted and could intercept and drop those messages. We describe a synchronous algorithm that ensures deterministic fair exchange if a majority of parties are honest, which is optim

We study the time-complexity of robust atomic read/write storage from fault-prone storage components in asynchronous message-passing systems. Robustness here means wait-free tolerating the largest possible number t of Byzantine storage component failures ( ...

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 ...

Failure detectors (FD)s are celebrated for their modularity in solving distributed problems. Algorithms are constructed using FD building blocks. Synchrony assumptions to implement FDs are studied separately and are typically expressed as eventual guarante ...

Similarity computations are crucial in various web activities like advertisements, search or trust-distrust predictions. These similarities often vary with time as product perception and popularity constantly change with users' evolving inclination. The hu ...

Many problems in distributed computing are impossible when no information about process failures is available. So what is the minimal yet non-trivial failure information? In other words, what is the minimal information about failures needed to circumvent a ...

Concurrency and failures are fundamental problems in distributed computing. One likes to think that the mechanisms needed to address these problems can be separated from the rest of the distributed application: in modern words, these mechanisms could be aspectized. Does this however make sense? This paper relates an experience that conveys our initial and indeed biased intuition that the answer is in general no. Except for simple academic examples, it is hard and even potentially dangerous to separate concu

The present invention concerns computer-implemented methods for training a machine learning model using Stochastic Gradient Descent, SGD. In one embodiment, the method is performed by a first computer in a distributed computing environment and comprises pe ...

The vast majority of papers on distributed computing assume that processes are assigned unique identifiers before computation begins. But is this assumption necessary? What if processes do not have unique identifiers or do not wish to divulge them for reasons of privacy? Here, we consider asynchronous shared-memory systems that are anonymous, which means processes do not have identifiers, and are programmed identically. The shared memory contains only the most common type of shared objects, read/write regis

Predicting the scalability of parallel applications is becoming crucial now that the number of cores in modern CPUs doubles roughly every two years. Traditional ways to get some understanding of the scalability of a parallel application rely on extensive experiments or detailed application models. Both are very time consuming and often hard to use. This paper presents PreSca, a pragmatic system for predicting the scalability of parallel applications. PreSca uses function approximation techniques to model sc

Recommenders, as widely implemented nowadays by major e-commerce players like Netflix or Amazon, use collaborative filtering to suggest the most relevant items to their users. Clearly, the effectiveness of recommenders depends on the data they can exploit, ...

The ubiquity of distributed machine learning (ML) in sensitive public domain applications calls for algorithms that protect data privacy, while being robust to faults and adversarial behaviors. Although privacy and robustness have been extensively studied ...

Rachid Guerraoui

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Type-Based Publish/Subscribe

Brief Announcement: A Case for Byzantine Machine Learning

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Democratizing Transactional Programming

Transactions in the Jungle

Efficacy of temporal and spatial abstraction for training accurate machine learning models: A case study in smart thermostats

Collision-Free Pattern Formation

Model checking transactional memories

Gracefully Degrading Fair Exchange with Security Modules

The complexity of robust atomic storage

Oracular Byzantine Reliable Broadcast

Probabilistic and temporal failure detectors for solving distributed problems

Capturing the Moment: Lightweight Similarity Computations

On The Weakest Failure Detector Ever

AOP: Does it Make Sense ? The Case of Concurrency and Failures

Byzantine machine learning

What Can Be Implemented Anonymously?

A Pragmatic Approach for Predicting the Scalability of Parallel Applications

Heterogeneous Recommendations: What You Might Like To Read After Watching Interstellar

On the Privacy-Robustness-Utility Trilemma in Distributed Learning