Swarm Differential Privacy for Purpose Driven Data Information Knowledge Wisdom Architecture

Privacy protection has recently attracted the attention of both academics and industry . Society protects individual data privacy through complex legalframeworks . Swarm Intelligence could effectively optimize and reduce thenumber of items in DIKW used in differential privacy . The proposed approach is proved through the application of personalized data that is based on the open-sourse IRIS dataset .…

Opening the Blackbox Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics

Current strategies to overcome slow prediction require high order automaticdifferentiation, leading to significantly higher training time . We describe anovel regularization method that uses internal cost heuristics of adaptivedifferential equation solvers combined with discrete adjoint sensitivities toguide the training process towards learning NDEs that are easier to solve .…

Non iterative Optimization Algorithm for Active Distribution Grids Considering Uncertainty of Feeder Parameters

A paper formulates a time-varying optimization problem for distribution grids with DERs and develops a novel non-iterative algorithm . Different from existing methods, the proposedapproach does not require iterations during the sampling interval . It only needs to perform a single one-step calculation at each interval to obtain theevolution of the optimal trajectory .…

Holomorphic feedforward networks

Feedforward neural network is a popular model in machine learning . The FFN can approximate general functions and mitigate the curse ofdimensionality . Here we introduce FFNs which represent sections of holomorphicline bundles on complex manifolds . We also explain formal similarities between the standardapproach to supervised learning and the problem of finding numerical Ricci flatK\”ahler metrics .…

Impacts of Privately Owned Electric Vehicles on Distribution System Resilience A Multi agent Optimization Approach

We investigate the effects of private electric vehicles (EVs) on the resilience of distribution systems after disruptions . We propose a framework of network-based multi-agent optimization problems with equilibrium constraints . To solve the high-dimensional non-convexproblem, we develop an efficient computational algorithm based on exact convexreformulation .…

Dataset and Performance Comparison of Deep Learning Architectures for Plum Detection and Robotic Harvesting

Robotic fruit harvesting is an important technology to address the increasing labourshortages and uncertainty suffered by tree crop growers . An eye-in-hand sensingsetup is commonly used in harvesting systems and provides benefits to sensingaccuracy and flexibility . However, as the hand and camera move from viewing theentire trellis to picking a specific fruit, large changes in lighting, colour, and exposure occur .…

Aerospace Sliding Mode Control Toolbox Relative Degree Approach with Resource Prospector Lander and Launch Vehicle Case Studies

Sliding mode control and observation techniques are widely used in aerospace applications, including aircrafts, UAVs, launch vehicles, missileinterceptors, and hypersonic missiles . This work is dedicated to creating aMATLAB-based sliding mode controller design and simulation software toolbox . The efficacy of the SMC Aero toolbox isconfirmed in two case studies: controlling and simulating resource prospectorlander (RPL) soft landing on the Moon and launch vehicle (LV) attitude control in ascent mode .…

Stochastic Multi Armed Bandits with Control Variates

This paper studies a new variant of the stochastic multi-armed banditsproblem, where the learner has access to auxiliary information about the arms . The auxiliary information is correlated with the arm rewards, which we treat as control variates . In many applications, the rewards are a function of someexogenous values, whose mean value is known a priori from historical data .…

Improving Multi agent Coordination by Learning to Estimate Contention

We present a multi-agent learning algorithm for efficient and fair allocations in large-scale systems . ALMA-Learning is decentralized, observes only own action/reward pairs, requires nointer-agent communication, and achieves near-optimal (<5% loss) and faircoordination in a variety of synthetic scenarios and a real-world meetingscheduling problem . The lightweight nature and fast learning constituteALma-Learning ideal for on-device deployment . …

Exploiting Path Information for Anchor Based Graph Neural Network

Graph Inference Representation (GIR) is an anchor based GNN encoding path information related to anchors for each node . We show that GIRs get outperformed results on position-aware scenario, and could improve GNNs results by fuse GIR’s embedding . Learning node representation that incorporating information from graphstructure benefits wide range of tasks on graph.…

FNet Mixing Tokens with Fourier Transforms

We show that Transformer encoder architectures can be massively sped up, with limited accuracy costs, by replacing the self-attention sublayers with simplelinear transformations that “mix” input tokens . The resulting model,which we name FNet, scales very efficiently to long inputs, matching the accuracy of the most accurate “efficient” Transformers on the Long Range Arenabenchmark, but training and running faster across all sequence lengths on GPUs .…

Advising Agent for Service Providing Live Chat Operators

Call centers, in which human operators attend clients using textual chat, are common in modern e-commerce . We suggest an algorithm and amethod to train and implement an assisting agent that provides on-line adviceto operators while they attend clients . The agent is domain-independent and canbe introduced to new domains without major efforts in design, training andorganizing structured knowledge of the professional discipline .…

Meta validation of bipartite network projections

Monopartite projections of bipartite networks are key tools to model indirectinteractions in complex systems . The standard approach to extract informativepatterns from these systems is to statistically validate them using a suitablenull network model . However different CM formulations exist, depending on how the degree constraints are imposed and for which nodes are nodes .…

High performance symbolic numerics via multiple dispatch

Symbolics.jl is an extendable symbolicsystem which uses dynamic multiple dispatch to change behavior depending on the domain needs . We show that byformalizing a generic API on actions independent of implementation, we can retroactively add optimized data structures to our system without changing thepre-existing term rewriters .…

Similarity Downselection A Python implementation of a heuristic search algorithm for finding the set of the n most dissimilar items with an application in conformer sampling

Finding the set of the n items most dissimilar from each other out of alarger population becomes increasingly difficult and computationally expensive . An exactsolution would have to search all possible combinations of size n in the population, exhaustively . We present an open-source software called similaritydownselection (SDS) written in Python and freely available on GitHub .…

Learning Image Attacks toward Vision Guided Autonomous Vehicles

This paper presents an online adversarial machine learning framework that can effectively misguide autonomous vehicles’ missions . The framework removes the need for fully converged optimization atevery frame to realize image attacks in real-time . Using reinforcementlearning, a generative neural network is trained over a set of image frames to obtain an attack policy that is more robust to dynamic and uncertain environments .…

Generative Mechanisms The mechanisms that implement codes

The purpose of this paper is to abstractly describe the notion of agenerative mechanism that implements a code . A generative mechanism is distinguishedfrom a selectionist mechanism that has heretofore played an important role in modeling (e.g., Darwinian evolution and the immune system) The paper provides examples of the DNA-RNA machinery that implements the genetic code, Chomsky’sPrinciples & Parameters model of a child acquiring a specific grammar given`chunks’ of linguistic experience .…

ReLie a Reduce program for Lie group analysis of differential equations

Lie symmetry analysis provides a theoretical framework for investigating ordinary and partial differential equations . The theory is algorithmic even if it usually involves lengthy computations . ReLie, written in the Computer Algebra System Reduce, is able to perform almost automatically the needed computations for Lie symmetric analysis of differential equations.…

Adaptive and Risk Aware Target Tracking with Heterogeneous Robot Teams

We consider a scenario where a team of robots with heterogeneous sensors must track a set of hostile targets . The likelihood of failures depends on the proximity between the targets and the robots . We propose a control framework that implicitly addresses the competing objectives of performance maximization and sensor preservation (which impacts the future performance of the team) Simulated experiments with induced sensor failures demonstrate the effectiveness of the proposed approach .…

Continuous representations of intents for dialogue systems

Intent modelling has become an important part of modern dialogue systems . Up until recently the focus has been on detecting a fixed,discrete, number of seen intents . This paper proposes a novel model where intents are continuous points placed in a specialist Intent Space that yields severaladvantages.…

D2S Document to Slide Generation Via Query Based Text Summarization

Presentations are critical for communication in all areas of our lives, yet the creation of slide decks is often tedious and time-consuming . We present D2S, a novel system that tackles the document-to-slides task with a two-step approach: 1)Use slide titles to retrieve relevant and engaging text, figures, and tables;2) Summarize the retrieved context into bullet points with long-form questionanswering.…

Coded Alternating Least Squares for Straggler Mitigation in Distributed Recommendations

Matrix factorization is an important representation learning algorithm, e.g.,recommender systems, where a large matrix can be factorized into the product of two low dimensional matrices termed as latent representations . This paper investigates the problem of matrix factorization in distributed computingsystems with stragglers, those compute nodes that are slow to returncomputation results .…

Improving Cross Lingual Reading Comprehension with Self Training

Previous works have revealed the abilities of pre-trainedmultilingual models for zero-shot cross-lingual reading comprehension . In thispaper, we further utilized unlabeled data to improve the performance . The experiment results showed improvementsfor all languages, and we also analyzed how self-training benefits the performance in qualitative aspects .…

MIMO Terahertz Quantum Key Distribution

We propose a multiple-input multiple-output (MIMO) quantum key distribution (QKD) scheme for improving the secret key rates and increasing the maximum transmission distance for terahertz (THz) frequency range applications . The MIMO transmission schemeprovides a multiplexing gain of $r$ along with a beamforming and array gain equal to the product of the number of transmit and receive antennas .…

Stochastic Properties of EIP 1559 Basefees

EIP-1559 is a new proposed pricing mechanism for the Ethereum protocoldeveloped to bring stability to fluctuating gas prices . To properly understand this as a stochastic process, it is necessary to develop the mathematical foundations to understand under what conditions the base fee gas price outcomes behave as a stationary process .…