Fair division of graphs and of tangled cakes

A tangle is a connected topological space constructed by gluing several copies of the unit interval $[0, 1] We explore which tangles guaranteeenvy-free allocations of connected shares for n agents . We show that exactly six tangles are stringable; these guarantee EFconnected allocations for any number of agents, and their associatedtopological classes contain only Hamiltonian graphs .…

A Lazy Approach for Efficient Index Learning

Learned indices using neural networks outperform traditional indices such as B-trees in both query time and memory . Learning the distribution of a large dataset can be expensive, and updatinglearned indices is difficult . We propose a novel approach toreuse these pre-trained models for a new (real) dataset .…

User Inspired Posterior Network for Recommendation Reason Generation

Recommendation reason generation plays a vital role in attracting customers’ attention and improving user experience . A simple and effective way is to extractkeywords directly from the knowledge-base of products, i.e., attributes ortitle, as the recommendation reason . But generating recommendation reason from product knowledge doesn’t naturally respond to users’ interests .…

Moral Decision Making in Medical Hybrid Intelligent Systems A Team Design Patterns Approach to the Bias Mitigation and Data Sharing Design Problems

Increasing automation in the healthcare sector calls for a HybridIntelligence (HI) approach to closely study and design the collaboration of humans and machines . Ensuring that medical HI systems’decision-making is ethical is key . The use of Team Design Patterns (TDPs) canadvance this goal by describing successful and reusable configurations ofdesign problems in which decisions have a moral component, as well as facilitating communication in multidisciplinary teams designing HI systems .…

Decidability for Sturmian words

We show that the theory of Sturmian words over Presburger arithmetic is decidable . We use a general adder recognizing addition in Ostrowski numeration systems by Baranwal, Schaeffer and Shallit . We then deduce the decidability of the first-order theory of the class of such structures .…

Follow the Regularized Leader Routes to Chaos in Routing Games

We study the emergence of chaotic behavior of Follow-the-Regularized Leader(FoReL) dynamics in games . We focus on the effects of increasing the populationsize or the scale of costs in congestion games . Although FoReL dynamics can be strange andnon-equilibrating, we prove that the time average still converges to an exact equilibrium for any choice of learning rate and any scale of cost .…

Finding the Gap Neuromorphic Motion Vision in Cluttered Environments

In the fly brain, motion-sensitive neurons indicate the presence of nearby objects and directional cues are integrated within an areaknown as the central complex . The agent’s manoeuvres result from a closed action-perception loop implementingprobabilistic decision-making processes . This loop-closure is thought to havedriven the development of neural circuitry in biological agents since the Cambrian explosion .…

Metatheory jl Fast and Elegant Algebraic Computation in Julia with Extensible Equality Saturation

Metatheory.jl is a lightweight and performant general purposesymbolics and metaprogramming framework . It is meant to simplify the act of writing complex Julia metaprograms and to significantly enhance Julia with a nativeterm rewriting system, based on state-of-the-art equality saturationtechniques, and a dynamic first class Abstract Syntax Tree (AST) patternmatching system that is dynamically composable in an algebraic fashion, taking advantage of the language’s powerful reflection capabilities .…

Data provenance curation and quality in metrology

Data metrology has emerged as an important requirement for UK National Physical Laboratory and other national metrologyinstitutes . Data provenance and data curation are key components for emergingunderstanding of data metrology . To date provenance research has had limited visibility to or uptake in metrology, authors say .…

C11Tester A Race Detector for C C Atomics Technical Report

C11Tester is a race detector for the C/C++ memory model . It can explore executions in a larger fragment of the memory model than previous race detector tools . It uses a new constraint-based algorithm to implementmodification order that is optimized to allow C11 tester to make decisions interms of application-visible behaviors .…

A Federated Data Driven Evolutionary Algorithm

Data-driven evolutionary optimization has witnessed great success in solving complex real-world optimization problems . However, existing data-drivenoptimization algorithms require that all data are centrally stored, which is not always practical and may be vulnerable to privacy leakage and security threats if the data must be collected from different devices .…

A Qualitative Theory of Cognitive Attitudes and their Change

We present a general logical framework for reasoning about agents’ cognitiveattitudes of both epistemic type and motivational type . We show that it allows us to express a variety of relevant concepts for qualitative decision theory . We also present twoextensions of the logic, one by the notion of choice and the other by dynamicoperators for belief change and desire change .…

Federated Multi armed Bandits with Personalization

A general framework of personalized federated multi-armed bandits (PF-MAB) is proposed . A mixed bandit learning problem flexibly balances generalization and personalization . Theoretical analysis proves that PF-UCB achieves an$O(\log(T)$ regret regardless of the degree of personalization, and has asimilar instance dependency as the lower bound .…

DFAC Framework Factorizing the Value Function via Quantile Mixture for Multi Agent Distributional Q Learning

In fully cooperative multi-agent reinforcement learning (MARL) settings, the environments are highly stochastic due to the partial observability of each agent and the continuously changing policies of the other agents . We propose a Distributional Value FunctionFactorization (DFAC) framework to generalize expected value functionfactorization methods to their DFAC variants .…

Unambiguous DNFs from Hex

We exhibit an unambiguous k-DNF formula that requires CNF widthOmega~(k^{1.5) Our construction is inspired by the board game Hex and it isvastly simpler than previous ones . Our result is known to imply several other improved separations in query andcommunication complexity .…

Metropolis Walks on Dynamic Graphs

We study a lazy Metropolis walk of Nonaka, Ono, Sadakane, and Yamashita(2010) which is a weighted random walk using local degree information . We show that this walk is robust to an edge-changing in dynamic networks . We give upper bounds of those times for any reversible random walks with a time-homogeneous stationary distribution.…

Quasi Monte Carlo Software

This article describes some of the better quasi-Monte Carlo (QMC) software available . We highlight the key software components required to approximate multivariate integrals . We have combined these components in QMCPy, a Python open source library . We hope to draw the support of the QMC community .…

Arboreal Categories An Axiomatic Theory of Resources

Arboreal categories have intrinsic process structure, allowing dynamic notions such as bisimulation and back-and-forth games to be defined . These are related to extensional structures via arboreal covers, which areresource-indexed comonadic adjunctions . These ideas are developed in a verygeneral, axiomatic setting, and applied to relational structures .…

Orchestrated Trios Compiling for Efficient Communication in Quantum Programs with 3 Qubit Gates

Current quantum computers are especially error prone and require high level optimization to reduce operation counts and maximize the probability the program will succeed . We propose a new compiler structure that first decomposes to the three-qubitToffoli, routes the inputs of the higher-level Toffoli operations to groups of qubits, then finishes decomposition to hardware-supported gates .…

Optimal intervention in traffic networks

We present an efficient algorithm to identify which edge should be improved in a traffic network to minimize the total travel time . We then study the optimality of the proposed procedure for recurrent networks, and provide simulations oversynthetic and real transportation networks .…

About Weighted Random Sampling in Preferential Attachment Models

The Barabasi-Albert model is a very popular model for creating randomscale-free graphs . Despite its widespread use, there is a subtle ambiguity inthe definition of the model and, consequently, the dependent models and applications . This ambiguity is a result of a tight relation with the field of unequal probability random sampling, which dictates the exact process of edge creation after a newborn node has been added .…

Compilation of mathematical expressions in Kotlin

KMath library uses the Kotlin object builder DSL and its own algebraic abstractions to generate an AST for mathematical operations . This AST is then compiled just-in-time to generate JVM bytecode . A similar approach is tested on other Kotlin platforms, where its performance is compared across avariety of supported platforms .…

On Greedily Packing Anchored Rectangles

Freedman [1969] posed this problem in 1969, asking whether one can always cover at least 50% of U . Dumitrescuand T\’oth [2011] achieved the first constant coverage of 9.1% . Authors could not find any instance where their algorithm covers less than 50% .…

Finite Atomized Semilattices

We show that every finite semilattice can be represented as an atomizedsemilattice . Each atom maps to one subdirectlyirreducible component, and the set of atoms forms a hypergraph that fully defines the semilatice . We also show that each atomization always exists and is unique up to “redundant atoms” The results can be applied to machine learning and to the study of semantic embeddings into algebras withidempotent operators .…

Maximizing Conditional Entropy for Batch Mode Active Learning of Perceptual Metrics

Active metric learning is the problem of incrementally selecting batches of training data (typically, ordered triplets) to annotate, in order toprogressively improve a learned model of a metric over some input domain asrapidly as possible . Standard approaches, which independently select eachtriplet in a batch, are susceptible to highly correlated batches with many redundant triplets and hence low overall utility .…

Prioritizing Original News on Facebook

This work outlines how we prioritize original news, a critical indicator of quality . By examining the landscape and life-cycle of news posts on our social media platform, we identify challenges of building and deploying anoriginality score . We pursue an approach based on normalized PageRank values and three-step clustering, and refresh the score on an hourly basis to capture the dynamics of online news .…

Annealed Flow Transport Monte Carlo

Annealed Importance Sampling (AIS) and its Sequential Monte Carlo (SMC)extensions are state-of-the-art methods for estimating normalizing constants of probability distributions . We propose a novel Monte Carlo algorithm,Annealed Flow Transport (AFT) that builds upon AIS and SMC and combines them with normalizing flows (NF) for improved performance .…