Hedonic Seat Arrangement Problems

In this paper, we study a variant of hedonic games called \textsc{SeatArrangement}. The model is defined by a bijection from agents with preferencesto vertices in a graph . We investigate the computational complexity of problems to find certain “good” seat arrangements .…

A New Minimax Theorem for Randomized Algorithms

The celebrated minimax principle of Yao (1977) says that for anyBoolean-valued function $f$ with finite domain, there is a distribution $mu$ that works for all bias levels at once . We show that this works for randomized query complexity, randomized communicationcomplexity, some randomized circuit models, quantum query and communicationcomplexities, approximate polynomial degree, and approximate logrank .…

Near Optimal Task Graph Scheduling with Priced Timed Automata and Priced Timed Markov Decision Processes

Task graph scheduling suffers from acombinatorial explosion and thus finding optimal schedulers is a difficult task . The task graph schedulingproblem is reduced to location reachability via the fastest path in PricedTimed Automata (PTA) and Priced Timed Markov Decision Processes (PTMDP) We conduct an exhaustive experimental evaluation where we compare our resulting schedules with the best-known schedules of a state of the art tool .…

G 1 hole filling with S patches made easy

S-patches have been around for 30 years, but they are seldom used, and are considered more of a mathematical curiosity than a practical surface representation . In this article a method is presented for automatically creating S-Patches of any degree or any number of sides, suitable for inclusion in a curve network with tangential continuity to the adjacent surfaces .…

Implicit Geometric Regularization for Learning Shapes

Representing shapes as level sets of neural networks has been recently proved useful for different shape analysis and reconstruction tasks . So far, such representations were computed using either: (i) pre-computed implicitshape representations; or (ii) loss functions explicitly defined over theneural level sets .…

FairRec Two Sided Fairness for Personalized Recommendations in Two Sided Platforms

We investigate the problem of fair recommendation in the context of two-sided online platforms, comprising customers on one side and producers on the other . We consider fairness issues that span both customers and producers . Our proposed FairRec algorithm guarantees at least Maximin Share (MMS) of exposure for most of the producers and Envy-Free up to One item (EF1) fairness for everycustomer.…

Double Spend Counterattacks Threat of Retaliation in Proof of Work Systems

Proof-of-Work mining is intended to provide blockchains with robustness against double-spend attacks . However, an economic analysis suggests that the resulting rewards can make an attack cheap . We formalize a defense to double spend attacks . We show that when the victim can counterattack in the same way as the attacker, this leads to a variation on the classic game-theoretic War of attrition model .…

Fair and Truthful Mechanisms for Dichotomous Valuations

We focus on valuationsthat have dichotomous marginals, in which the added value of any item to a setis either 0 or 1 . We aim to design truthful allocation mechanisms (without money) that maximize welfare and are fair . We then show that our mechanism withrandom priorities is envy-free ex-ante, while having all the above propertiesex-post .…

Inducing Equilibria in Networked Public Goods Games through Network Structure Modification

Networked public goods games model scenarios in which self-interested agents decide whether or how much to invest in an action that benefits their network neighbors . Examples include vaccination, security investment, and crime reporting . We show that the problem is NP-complete for a number of scenarios, but we exhibit a broadarray of scenarios where the problem can be solved in polynomial time by reducing the problem to (minimum-cost) matching problems .…

Weighted PCL over product valuation monoids

We introduce a weighted propositional configuration logic over a productvaluation monoid . Our logic is intended to serve as a specification language for software architecture with quantitative features such as the average of interactions’ costs of the architecture . We provide formulas of our logic which describe well-knownarchitectures equipped with quantitative characteristics .…

A Type Checker for a Logical Framework with Union and Intersection Types

Bull is a prototypetheorem prover based on the Delta-Framework, i.e. a fully-typed lambda-calculus decorated with union and intersection types . Bull implements a subtyping algorithm for the Type Theory Xiof Barbanera-Dezani-de’Liguoro . Bull uses a higher-order unification algorithm for terms, while typechecking and partial type inference are done by abidirectional refinement algorithm, similar to the one found in Matita andBeluga .…

Model Watermarking for Image Processing Networks

Deep learning has achieved tremendous success in numerous industrial applications . However, these valuable deep models are exposed to a huge risk ofinfringements . How toprotect the intellectual property of deep models is a very important butseriously under-researched problem . In this paper, we propose the firstmodel watermarking framework for protecting image processing models .…

DDet Dual path Dynamic Enhancement Network for Real World Image Super Resolution

Real-SR focus on relationship between real-worldhigh-resolution(HR) and low-resolution (LR) image . Most of the traditional imageSR obtains the LR sample by applying a fixed down-sampling operator . In this article, we propose a Dual-path Dynamic Enhancement Network(DDet), which addresses the cross-camera image mapping by realizing a dual-way dynamicsub-pixel weighted aggregation and refinement .…

Model based Joint Bit Allocation between Geometry and Color for Video based 3D Point Cloud Compression

Rate distortion optimization plays a very important role in image/videocoding . In thispaper, the rate and distortion characteristics of 3D point cloud are investigated in detail . To maximize the reconstructed quality of the reconstructed 3Dpoint cloud, the bit allocation problem is formulated as a constrainedoptimization problem and solved by an interior point method .…

Engaging Users through Social Media in Public Libraries

The participatory library is an emerging concept which refers to the ideathat an integrated library system must allow users to take part in core functions of the library rather than engaging on the periphery . To embrace theparticipatory idea, libraries have employed many technologies, such as socialmedia to help them build participatory services and engage users .…

LibrettOS A Dynamically Adaptable Multiserver Library OS

LibrettOS fuses two paradigms to simultaneously address issues of isolation, performance, compatibility, failurerecoverability, and run-time upgrades . The OS acts as a microkernel OS that runs servers in an isolated manner . It can also act as a library OS when applications are granted exclusive access to virtual hardware resources such as storage and networking .…

MLIR A Compiler Infrastructure for the End of Moore s Law

MLIR aims to address software fragmentation, improve compilation for heterogeneous hardware, significantly reduce the cost of building domain specific compilers, and aid in connecting existing compilers . MLIR facilitates the design and implementation of code generators,translators and optimizers at different levels of abstraction and also across application domains, hardware targets and execution environments .…

On the complexity of zero gap MIP

The class $\mathsf{MIP}^*$ is the set of languages decidable by multiproverinteractive proofs with quantum entangled provers . In this paper we investigate the complexity of deciding whether the quantumvalue of a non-local game $G$ is exactly $1$ This problem corresponds to acomplexity class that we call zero gap $MIP##$ .…

Fast In place Algorithms for Polynomial Operations Division Evaluation Interpolation

We consider space-saving versions of several important operations onunivariate polynomials . We demonstrate new in-place algorithms for theaforementioned polynomial computations which require only constant extra space . We also provide a precise complexity analysis so that allconstants are made explicit, parameterized by the space usage of the underlyingmultiplication algorithms .…

Lower bounds for prams over Z

Paper presents a new abstract method for proving lower bounds incomputational complexity . Based on the notion of topological entropy fordynamical systems, the method captures four previous lower bounds results from the literature in algebraic complexity . Among these results lies Mulmuley’s proof that “prams without bit operations” do not compute the maxflow problem inpolylogarithmic time .…

Wheeler Languages

Wheeler graphs are inspired by the Burrows-Wheeler Transform (BWT) of a given string . They admit an efficient index data structure for searching for subpaths with a given path label . We study languages accepted by automata having aWheeler graph as transition function .…

PolyGen An Autoregressive Generative Model of 3D Meshes

Polygon meshes are an efficient representation of 3D geometry, and are of central importance in computer graphics, robotics and games development . We present an approach which models the mesh directly, predicting mesh vertices and faces . Our model can condition on a range of inputs, including object classes, voxels, and images, and can produce samples that capture uncertainty in ambiguous scenarios .…

Image Stylization From Predefined to Personalized

We present a framework for interactive design of new image stylizations using a wide range of predefined filter blocks . Both novel and off-the-shelf imagefiltering and rendering techniques are extended and combined to allow the userto unleash their creativity to invent, modify, and tune new styles .…

Equitable Allocations of Indivisible Chores

We study fair allocation of indivisible chores among agents with additive valuations . An allocation is deemed fair if it is (approximately) equitable, which means that the disutilities of the agents are (about) equal . We show that there always exists an allocation that is simultaneously equitable up toone chore (EQ1) and Pareto optimal (PO) Our experiments on synthetic as well as real-world data show that the algorithms considered in ourwork satisfy approximate fairness and efficiency properties significantly more often than the algorithm currently deployed on Spliddit.…

Efficient exploration of zero sum stochastic games

We investigate the increasingly important and common game-solving setting where we do not have an explicit description of the game but only oracle accessto it through gameplay . We propose using the distribution of state-action value functions induced by a belief distribution over possible environments .…

Optimal Advertising for Information Products

When selling information, sometimes the seller can increase the revenue by giving away some partial information to change the buyers’ belief about the product . This workstudies the general problem of advertising information products by revealingsome partial information . The seller’s goal is to maximize the expected revenue .…

Scalable Multi Agent Inverse Reinforcement Learning via Actor Attention Critic

Multi-agent adversarial inverse reinforcement learning (MA-AIRL) is a recent approach that applies single-agent AIRL to multi-agent problems where we seek to recover both policies for our agents and reward functions that promoteexpert-like behavior . While MA-AIRl has promising results on cooperative andcompetitive tasks, it is sample-inefficient and has only been validatedempirically for small numbers of agents — its ability to scale to many agents remains an open question .…

Bio inspired Optimization metaheuristic algorithms for optimization

In today’s day and time solving real-world complex problems has become vital and critical task . Many of these are combinatorial problems, where optimal solutions are sought rather than exact solutions . Last two decades have seen many new methods in AI based on the characteristics and behaviors of the living organisms in thenature which are categorized as bio-inspired or nature inspired optimizational algorithms .…

APAC Net Alternating the Population and Agent Control via Two Neural Networks to Solve High Dimensional Stochastic Mean Field Games

APAC-Net is an alternating population and agent control neuralnetwork for solving stochastic mean field games (MFGs) Our algorithm is gearedtoward high-dimensional instances of MFGs that are beyond reach with existingsolution methods . We show the potential of our method on up to 100-dimensional MFG problems, we show potential of the algorithm on up-to-100-dimensional problems .…