Roger Wattenhofer's research while affiliated with ETH Zurich and other places

Publications (563)

Preprint
Full-text available
The learning of the simplest possible computational pattern -- periodicity -- is an open problem in the research of strong generalisation in neural networks. We formalise the problem of extrapolative generalisation for periodic signals and systematically investigate the generalisation abilities of classical, population-based, and recently proposed...
Preprint
Full-text available
Integer sequences are of central importance to the modeling of concepts admitting complete finitary descriptions. We introduce a novel view on the learning of such concepts and lay down a set of benchmarking tasks aimed at conceptual understanding by machine learning models. These tasks indirectly assess model ability to abstract, and challenge the...
Article
Full-text available
Live Streaming Commerce (LSC) is proliferating in China and gaining traction worldwide. LSC is an e-commerce service where sellers communicate with consumers through live streaming while consumers can place orders within the same system. Despite the significant involvement of consumers in LSC, it has not been systematically analyzed how consumers m...
Preprint
Within just four years, the blockchain-based Decentralized Finance (DeFi) ecosystem has accumulated a peak total value locked (TVL) of more than 253 billion USD. This surge in DeFi's popularity has, unfortunately, been accompanied by many impactful incidents. According to our data, users, liquidity providers, speculators, and protocol operators suf...
Preprint
Full-text available
Owing to their versatility, graph structures admit representations of intricate relationships between the separate entities comprising the data. We formalise the notion of connection between two vertex sets in terms of edge and vertex features by introducing graph-walking programs. We give two algorithms for mining of deterministic graph-walking pr...
Preprint
Financial markets have evolved over centuries, and exchanges have converged to rely on the order book mechanism for market making. Latency on the blockchain, however, has prevented decentralized exchanges (DEXes) from utilizing the order book mechanism and instead gave rise to the development of market designs that are better suited to a blockchain...
Preprint
A distributed directory is an overlay data structure on a graph $G$ that helps to access a shared token $t$. The directory supports three operations: publish, to announce the token, lookup, to read the contents of the token, and move, to get exclusive update access to the token. The directory is built upon a hierarchical partition of the graph usin...
Conference Paper
We introduce two-crossing elections as a generalization of single-crossing elections, showing a number of new results. First, we show that two-crossing elections can be recognized in polynomial time, by reduction to the well-studied consecutive ones problem. Single-crossing elections exhibit a transitive majority relation, from which many important...
Preprint
Full-text available
We present a novel graph neural network we call AgentNet, which is designed specifically for graph-level tasks. AgentNet is inspired by sublinear algorithms, featuring a computational complexity that is independent of the graph size. The architecture of AgentNet differs fundamentally from the architectures of known graph neural networks. In AgentNe...
Preprint
This work proposes a novel proof-of-work blockchain incentive scheme such that, barring exogenous motivations, following the protocol is guaranteed to be the optimal strategy for miners. Our blockchain takes the form of a directed acyclic graph, resulting in improvements with respect to throughput and speed. More importantly, for our blockchain to...
Preprint
Full-text available
The collection of eye gaze information provides a window into many critical aspects of human cognition, health and behaviour. Additionally, many neuroscientific studies complement the behavioural information gained from eye tracking with the high temporal resolution and neurophysiological markers provided by electroencephalography (EEG). One of the...
Preprint
This paper studies the question whether automated market maker protocols such as Uniswap can sustainably retain a portion of their trading fees for the protocol. We approach the problem by modelling how to optimally choose a pool's take rate, i.e\ the fraction of fee revenue that remains with the protocol, in order to maximize the protocol's revenu...
Preprint
Full-text available
Most Graph Neural Networks (GNNs) cannot distinguish some graphs or indeed some pairs of nodes within a graph. This makes it impossible to solve certain classification tasks. However, adding additional node features to these models can resolve this problem. We introduce several such augmentations, including (i) positional node embeddings, (ii) cano...
Preprint
We propose the fully explainable Decision Tree Graph Neural Network (DT+GNN) architecture. In contrast to existing black-box GNNs and post-hoc explanation methods, the reasoning of DT+GNN can be inspected at every step. To achieve this, we first construct a differentiable GNN layer, which uses a categorical state space for nodes and messages. This...
Preprint
This paper studies asynchronous message passing (AMP), a new paradigm for applying neural network based learning to graphs. Existing graph neural networks use the synchronous distributed computing model and aggregate their neighbors in each round, which causes problems such as oversmoothing and limits their expressiveness. On the other hand, AMP is...
Preprint
Trade execution on Decentralized Exchanges (DEXes) is automatic and does not require individual buy and sell orders to be matched. Instead, liquidity aggregated in pools from individual liquidity providers enables trading between cryptocurrencies. The largest DEX measured by trading volume, Uniswap V3, promises a DEX design optimized for capital ef...
Preprint
We introduce two-crossing elections as a generalization of single-crossing elections, showing a number of new results. First, we show that two-crossing elections can be recognized in polynomial time, by reduction to the well-studied consecutive ones problem. We also conjecture that recognizing $k$-crossing elections is NP-complete in general, provi...
Preprint
Combinatorial auctions (CAs) allow bidders to express complex preferences for bundles of goods being auctioned. However, the behavior of bidders under different payment rules is often unclear. In this paper, we aim to understand how core constraints interact with different core-selecting payment rules. In particular, we examine the natural and desi...
Preprint
Full-text available
We approach the graph generation problem from a spectral perspective by first generating the dominant parts of the graph Laplacian spectrum and then building a graph matching these eigenvalues and eigenvectors. Spectral conditioning allows for direct modeling of the global and local graph structure and helps to overcome the expressivity and mode co...
Preprint
We empirically study the state of three prominent DAO governance systems on the Ethereum blockchain: Compound, Uniswap and ENS. In particular, we examine how the voting power is distributed in these systems. Using a comprehensive dataset of all governance token holders, delegates, proposals and votes, we analyze who holds the voting rights and how...
Preprint
User transactions on Ethereum's peer-to-peer network are at risk of being attacked. The smart contracts building decentralized finance (DeFi) have introduced a new transaction ordering dependency to the Ethereum blockchain. As a result, attackers can profit from front- and back-running transactions. Multiple approaches to mitigate transaction reord...
Preprint
Decentralized exchanges are revolutionizing finance. With their ever-growing increase in popularity, a natural question that begs to be asked is: how efficient are these new markets? We find that nearly 30% of analyzed trades are executed at an unfavorable rate. Additionally, we observe that, especially during the DeFi summer in 2020, price inaccur...
Preprint
Full-text available
We investigate the problem of Min-cost Perfect Matching with Delays (MPMD) in which requests are pairwise matched in an online fashion with the objective to minimize the sum of space cost and time cost. Though linear-MPMD (i.e., time cost is linear in delay) has been thoroughly studied in the literature, it does not well model impatient requests th...
Preprint
Digital money can be implemented efficiently by avoiding consensus. However, no-consensus implementations have drawbacks, as they cannot support smart contracts, and (even more fundamentally) they cannot deal with conflicting transactions. We present a novel protocol that combines the benefits of an asynchronous, broadcast-based digital currency, w...
Preprint
Predatory trading bots lurking in Ethereum's mempool present invisible taxation of traders on automated market makers (AMMs). AMM traders specify a slippage tolerance to indicate the maximum price movement they are willing to accept. This way, traders avoid automatic transaction failure in case of small price movements before their trade request ex...
Preprint
We study and compare different Graph Neural Network extensions that increase the expressive power of GNNs beyond the Weisfeiler-Leman test. We focus on (i) GNNs based on higher order WL methods, (ii) GNNs that preprocess small substructures in the graph, (iii) GNNs that preprocess the graph up to a small radius, and (iv) GNNs that slightly perturb...
Preprint
We consider the problem of finding a compromise between the opinions of a group of individuals on a number of mutually independent, binary topics. In this paper, we quantify the loss in representativeness that results from requiring the outcome to have majority support, in other words, the "price of majority support". Each individual is assumed to...
Article
Full-text available
The reconfiguration problem is considered a key challenge in distributed systems, especially in dynamic asynchronous message-passing systems. To keep the data reliability and availability in long-lived systems, any protocols should support reconfigurations, to dynamically add resources, or remove old and slow machines with newer faster ones. Previo...
Chapter
Flashcards, or any sort of question-answer pairs, are a fundamental tool in education. However, the creation of question-answer pairs is a tedious job which often defers independent learners from properly studying a topic. We seek to provide a tool to automatically generate flashcards from Wikipedia articles to make independent education more attra...
Preprint
This paper studies Dropout Graph Neural Networks (DropGNNs), a new approach that aims to overcome the limitations of standard GNN frameworks. In DropGNNs, we execute multiple runs of a GNN on the input graph, with some of the nodes randomly and independently dropped in each of these runs. Then, we combine the results of these runs to obtain the fin...
Chapter
We introduce a new permissionless blockchain architecture called Cascade (Consensusless, Asynchronous, Scalable, Deterministic and Efficient). The protocol is completely asynchronous, and does rely on neither randomness nor proof-of-work. Transactions exhibit finality within one round trip of communication.
Preprint
Full-text available
We present a new dataset and benchmark with the goal of advancing research in the intersection of brain activities and eye movements. Our dataset, EEGEyeNet, consists of simultaneous Electroencephalography (EEG) and Eye-tracking (ET) recordings from 356 different subjects collected from three different experimental paradigms. Using this dataset, we...
Preprint
Full-text available
3D reconstruction aims to reconstruct 3D objects from 2D views. Previous works for 3D reconstruction mainly focus on feature matching between views or using CNNs as backbones. Recently, Transformers have been shown effective in multiple applications of computer vision. However, whether or not Transformers can be used for 3D reconstruction is still...
Chapter
A Hashed Time Lock Contract (HTLC) is a central concept in cryptocurrencies where some value can be spent either with the preimage of a public hash by one party (Bob) or after a timelock expires by another party (Alice). We present a bribery attack on HTLC’s where Bob’s hash-protected transaction is censored by Alice’s timelocked transaction. Alice...
Chapter
Off-chain protocols (channels) are a promising solution to the scalability and privacy challenges of blockchain payments. Current proposals, however, require synchrony assumptions to preserve the safety of a channel, leaking to an adversary the exact amount of time needed to control the network for a successful attack. In this paper, we introduce B...
Preprint
Different studies of the embedding space of transformer models suggest that the distribution of contextual representations is highly anisotropic - the embeddings are distributed in a narrow cone. Meanwhile, static word representations (e.g., Word2Vec or GloVe) have been shown to benefit from isotropic spaces. Therefore, previous work has developed...
Preprint
Full-text available
Large pre-trained language models have repeatedly shown their ability to produce fluent text. Yet even when starting from a prompt, generation can continue in many plausible directions. Current decoding methods with the goal of controlling generation, e.g., to ensure specific words are included, either require additional models or fine-tuning, or w...
Preprint
Full-text available
Deep Neural Networks have taken Natural Language Processing by storm. While this led to incredible improvements across many tasks, it also initiated a new research field, questioning the robustness of these neural networks by attacking them. In this paper, we investigate four word substitution-based attacks on BERT. We combine a human evaluation of...
Preprint
In this paper, we study $k$-Way Min-cost Perfect Matching with Delays - the $k$-MPMD problem. This problem considers a metric space with $n$ nodes. Requests arrive at these nodes in an online fashion. The task is to match these requests into sets of exactly $k$, such that the space and time cost of all matched requests are minimized. The notion of...
Chapter
Meta-learning, transfer learning and multi-task learning have recently laid a path towards more generally applicable reinforcement learning agents that are not limited to a single task. However, most existing approaches implicitly assume a uniform similarity between tasks. We argue that this assumption is limiting in settings where the relationship...
Preprint
We present Accept, a simple, asynchronous transaction system that achieves perfect horizontal scaling. Usual blockchain-based transaction systems come with a fundamental throughput limitation as they require that all (potentially unrelated) transactions must be totally ordered. Such solutions thus require serious compromises or are outright unsuita...
Preprint
This paper introduces the Two-Class ($r$,$k$)-Coloring problem: Given a fixed number of $k$ colors, such that only $r$ of these $k$ colors allow conflicts, what is the minimal number of conflicts incurred by an optimal coloring of the graph? We establish that the family of Two-Class ($r$,$k$)-Coloring problems is NP-complete for any $k \geq 2$ when...
Preprint
Full-text available
This paper improves the robustness of the pretrained language model BERT against word substitution-based adversarial attacks by leveraging self-supervised contrastive learning with adversarial perturbations. One advantage of our method compared to previous works is that it is capable of improving model robustness without using any labels. Additiona...
Preprint
We study the stabilization time of two common types of influence propagation. In majority processes, nodes in a graph want to switch to the most frequent state in their neighborhood, while in minority processes, nodes want to switch to the least frequent state in their neighborhood. We consider the sequential model of these processes, and assume th...
Preprint
Full-text available
We consider networks of banks with assets and liabilities. Some banks may be insolvent, and a central bank can decide which insolvent banks, if any, to bail out. We view bailouts as an optimization problem where the central bank has given resources at its disposal and an objective it wants to maximize. We show that under various assumptions and for...
Chapter
We study the problem of evacuating two agents from a tree graph, through an unknown exit located at one of the nodes. Initially, the agents are located at the same starting node; they explore the graph until one of them finds the exit through which they can evacuate. The task is to minimize the time it takes until both agents evacuate, for a worst...
Preprint
We study financial networks where banks are connected by debt contracts. We consider the operation of debt swapping when two creditor banks decide to exchange an incoming payment obligation, thus leading to a locally different network structure. We say that a swap is positive if it is beneficial for both of the banks involved; we can interpret this...
Preprint
Full-text available
Decentralized exchanges (DEXes) have introduced an innovative trading mechanism, where it is not necessary to match buy-orders and sell-orders to execute a trade. DEXes execute each trade individually, and the exchange rate is automatically determined by the ratio of assets reserved in the market. Therefore, apart from trading, financial players ca...
Preprint
We suggest a framework to determine optimal trading fees for constant function market makers (CFMMs) in order to maximize liquidity provider returns. In a setting of multiple competing liquidity pools, we show that no race to the bottom occurs, but instead pure Nash equilibria of optimal fees exist. We theoretically prove the existence of these equ...
Preprint
Full-text available
Digital money is getting a lot of traction recently, a process which may accelerate even more with the advent of Central Bank Digital Currency (CBDC). Digital money has several disadvantages: Payments are difficult or outright impossible in emergency situations such as the failure of the electricity grid or Internet. CBDC may also be difficult to h...
Preprint
Full-text available
In May 2020, Uniswap V2 was officially launched on Ethereum. Uniswap V2 allows users to create trading pools between any pair of cryptocurrencies, without the need for ETH as an intermediary currency. Uniswap V2 introduces new arbitrage opportunities: Traders are now able to trade cryptocurrencies cyclically: A trader can exchange currency A for B,...
Preprint
Automatic ICD coding is the task of assigning codes from the International Classification of Diseases (ICD) to medical notes. These codes describe the state of the patient and have multiple applications, e.g., computer-assisted diagnosis or epidemiological studies. ICD coding is a challenging task due to the complexity and length of medical notes....
Preprint
Graph Neural Networks (GNNs) are the first choice for learning algorithms on graph data. GNNs promise to integrate (i) node features as well as (ii) edge information in an end-to-end learning algorithm. How does this promise work out practically? In this paper, we study to what extend GNNs are necessary to solve prominent graph classification probl...
Preprint
Full-text available
We study the problem of adversarially robust self-supervised learning on graphs. In the contrastive learning framework, we introduce a new method that increases the adversarial robustness of the learned representations through i) adversarial transformations and ii) transformations that not only remove but also insert edges. We evaluate the learned...
Preprint
A set of mutually distrusting participants that want to agree on a common opinion must solve an instance of a Byzantine agreement problem. These problems have been extensively studied in the literature. However, most of the existing solutions assume that the participants are aware of $n$ -- the total number of participants in the system -- and $f$...
Preprint
In this work we provide new insights into the transformer architecture, and in particular, its best-known variant, BERT. First, we propose a method to measure the degree of non-linearity of different elements of transformers. Next, we focus our investigation on the feed-forward networks (FFN) inside transformers, which contain 2/3 of the model para...
Preprint
Full-text available
We present Knowledge Enhanced Multimodal BART (KM-BART), which is a Transformer-based sequence-to-sequence model capable of reasoning about commonsense knowledge from multimodal inputs of images and texts. We extend the popular BART architecture to a multi-modal model. We design a new pretraining task to improve the model performance on Visual Comm...