New research reveals diverse cascade sizes in finite networks, challenging traditional risk assessments.
arXiv research
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On many social networking web sites such as Facebook and Twitter, resharing or reposting functionality allows users to share others' content with their own friends or followers. As content is reshared from user to user, large cascades of reshares can form. While a growing body of research has focused on analyzing and c…
We analyze cascades of defaults in an interbank loan market. The novel feature of this study is that the network structure and the size distribution of banks are derived from empirical data. We find that the ability of a defaulted institution to start a cascade depends on an interplay of shock size and connectivity. Fu…
External or internal shocks may lead to the collapse of a system consisting of many agents. If the shock hits only one agent initially and causes it to fail, this can induce a cascade of failures among neighoring agents. Several critical constellations determine whether this cascade remains finite or reaches the size o…
We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (e.g., …
A probabilistic framework is introduced that represents stylized banking networks and aims to predict the size of contagion events. In contrast to previous work on random financial networks, which assumes independent connections between banks, the possibility of disassortative edge probabilities (an above average tende…
I show the equivalence between a model of financial contagion and the threshold model of global cascades proposed by Watts (2002). The model financial network comprises banks that hold risky external assets as well as interbank assets. It is shown that a simple threshold model can replicate the size and the frequency o…
Structured prediction tasks pose a fundamental trade-off between the need for model complexity to increase predictive power and the limited computational resources for inference in the exponentially-sized output spaces such models require. We formulate and develop the Structured Prediction Cascade architecture: a seque…
Method certifies edge predictions with cloud-level reliability.
In an adaptive population which models financial markets and distributed control, we consider how the dynamics depends on the diversity of the agents' initial preferences of strategies. When the diversity decreases, more agents tend to adapt their strategies together. This change in the environment results in dynamical…
We study simultaneous price drops of real stocks and show that for high drop thresholds they follow a power-law distribution. To reproduce these collective downturns, we propose a minimal self-organized model of cascade spreading based on a probabilistic response of the system elements to stress conditions. This model …
We consider the problem of finding the graph on which an epidemic cascade spreads, given only the times when each node gets infected. While this is a problem of importance in several contexts -- offline and online social networks, e-commerce, epidemiology, vulnerabilities in infrastructure networks -- there has been ve…
A new approach reduces the size of prediction sets in CP, making it more efficient.
Algorithm estimates clock in network cascades to improve performance.
Modeling default contagion and systemic risk using a balls-and-bins approach.
We consider a model of financial contagion in a bipartite network of assets and banks recently introduced in the literature, and we study the effect of power law distributions of degree and balance-sheet size on the stability of the system. Relative to the benchmark case of banks with homogeneous degrees and balance-sh…
In the 'Big Data' era, many real-world applications like search involve the ranking problem for a large number of items. It is important to obtain effective ranking results and at the same time obtain the results efficiently in a timely manner for providing good user experience and saving computational costs. Valuable …
We study cascades on a two-layer multiplex network, with asymmetric feedback that depends on the coupling strength between the layers. Based on an analytical branching process approximation, we calculate the systemic risk measured by the final fraction of failed nodes on a reference layer. The results are compared with…
The American economy can be thought of as a highly connected random network in terms of both its technological and informational connections. The cumulative size of economic recessions, the fall in output from peak to trough, is analysed for the US economy 1900-2002. A least squares fit of an exponential relationship b…
Framework for multi-scale clustering using phase transitions.
Two algorithms improve performance in piecewise-stationary cascading bandits.
Method predicts diffusion reach probabilities using node embeddings.
This paper optimizes power grid protection settings to maximize network degradation due to cascading attacks.
Model infers diffusion networks from heterogeneous cascade data.
New insights into cascade feedback linearization of control systems.
The paper improves theoretical guarantees for Thompson Sampling in cascading bandits.
Modeling cascading behavior in complex systems using CTBNs.
We present a set of models of the main stylized facts of market price fluctuations. These models comprise dynamical evolution with threshold dynamics and Langevin price equation with multiplicative noise, percolation models to describe the interaction between traders and hierarchical cascade models to unravel the possi…
Study on information cascade fragility under mismatched revealing probabilities.
A search engine usually outputs a list of web pages. The user examines this list, from the first web page to the last, and chooses the first attractive page. This model of user behavior is known as the cascade model. In this paper, we propose cascading bandits, a learning variant of the cascade model where the obje…
Paper uses RL to mitigate cascading failures in power systems.
Bayesian optimization tackles expensive cascade processes.
Model shows financial turbulence similar to turbulence, with wealth cascading from large to small entities.
Cascades of information-sharing are a primary mechanism by which content reaches its audience on social media, and an active line of research has studied how such cascades, which form as content is reshared from person to person, develop and subside. In this paper, we perform a large-scale analysis of cascades on Faceb…
The paper improves methods for estimating set size using samples.
Modeling social network activity through user and topic interaction.
The paper addresses the -tangle enumeration problem. We introduce a notion of cascade diagram for -tangle projections. An effective enumeration algorithm for projections is proposed based on cascade representation. Tangles projections with up to 12 crossings are tabulated. We provide also pictures of alternating …
Information spreads across social and technological networks, but often the network structures are hidden from us and we only observe the traces left by the diffusion processes, called cascades. Can we recover the hidden network structures from these observed cascades? What kind of cascades and how many cascades do we …
DICE estimates data influence cascade in decentralized learning networks.
Unified approach for influence maximization using diffusion cascade representations.
Improves information cascade models using contrastive training and DSTs.
In this paper, we present a new approach to learning cascaded classifiers for use in computing environments that involve networks of heterogeneous and resource-constrained, low-power embedded compute and sensing nodes. We present a generalization of the classical linear detection cascade to the case of tree-structured …
Paper presents a probabilistic model to improve LLM cascade performance.
Model explains financial market intermittency with negative correlation.
Model financial default cascades on sparse graphs via hitting times.
A model infers dynamic networks from partial observation of cascading processes.
Develops a novel framework for activity shaping in social networks.
Cascading flows improve variational inference in structured programs.