B. Apolloni

B. Apolloni
University of Milan | UNIMI · Department of Computer Science

About

221
Publications
13,299
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1,284
Citations
Citations since 2017
19 Research Items
361 Citations
2017201820192020202120222023020406080
2017201820192020202120222023020406080
2017201820192020202120222023020406080
2017201820192020202120222023020406080
Additional affiliations
January 1990 - present
University of Milan
Position
  • Professor (Full)

Publications

Publications (221)
Chapter
As compatibility is a key issue of this book, the starting point is the observed data. In this chapter we provide a general model of them, as well as a consequent general approach to derive distributions of parameters determining compatible descriptions of them. A description may be delivered either in terms of the data distributions (inferring dis...
Chapter
Abandoning any pretence of knowing the Truth, I discuss in this chapter my approach to delineating a world that’s compatible with what I personally experienced. Since there’s infinitely more to the world than what I have experienced of it, I look for a possible infinite family of worlds that I may singularly characterize with a distinct degree of c...
Chapter
As it has emerged from the previous chapters, the golden kit allows for compatible worlds running both in monolithic and in distributed mode. Both are based on the platinum triangle computation-communication-memory architecture and on cognitive algorithms. The main distinction concerns the objective function: (i) either in favor of a few stakeholde...
Chapter
In this first chapter we start addressing the goal of understanding the surrounding Nature by starting from ourselves as a part of the Nature implementing of the goal. The core is represented by the pair genome plus synapses, to which we refer henceforth as the golden kit. In very basic terms, we refer to the former as a dynamic database from which...
Chapter
In worlds that are compatible with the assumption that we have overall visibility of it and the m data we observe appear without any constriction, so that they have the same relevance 1/m, probabilistic models are the landlords. Rather, if we have a limited scope we must ask other people to add data within their scope, and the relevance of the over...
Article
Full-text available
The regulatory role of the Micro-RNAs (miRNAs) in the messenger RNAs (mRNAs) gene expression is well understood by the biologists since some decades, even though the delving into specific aspects is in progress. In this paper we will focus on miRNA-mRNA modules, where regulation jointly occurs in miRNA-mRNA pairs. Namely, we propose a holistic proc...
Article
We introduce unprecedented tools to infer approximate evolution features of the COVID19 outbreak when these features are altered by containment measures. In this framework we present: 1) a basic tool to deal with samples that are both truncated and non independently drawn, and 2) a two-phase random variable to capture a game changer along a process...
Chapter
Full-text available
We study in a quantitative way the efficacy of a social intelligence scheme that is an extension of Extreme Learning Machine paradigm. The key question we investigate is whether and how a collection of elementary learning parcels can replace a single algorithm that is well suited to learn a relatively complex function. Per se, the question is defin...
Article
Full-text available
We formulate a new family of bootstrap algorithms suitable for learning non-Boolean functions from data. Within the Algorithmic Inference framework, the key idea is to consider a population of functions that are compatible with the observed sample. We generate items of this population from standard random seeds and reverse seed probabilities on the...
Conference Paper
Full-text available
This paper discusses a statistical analysis emerging in the field entrepreneurship education, as a result of a survey conducted in the frame of the European Project NETT (Networked Entrepreneurship Training of Teachers, http://nett-project.eu). The analysis concerns both the quality of data and the emergence of some special patterns denoting some i...
Article
Full-text available
In order to early forecast the local evolution of Covid19 epidemic, we introduce a pseudo-static model based on the equilibrium distribution of a two phase model. A first phase where the virus spreads without any containment measures followed by a phase where its spread is properly constrained. We identify the former with a process without memory a...
Preprint
Full-text available
We introduce a new method for estimating the parameter of the bivariate Clayton copulas within the framework of Algorithmic Inference. The method consists of a variant of the standard boot-strapping procedure for inferring random parameters, which we expressly devise to bypass the two pitfalls of this specific instance: the non independence of the...
Article
We discuss a Cloud-based Collective Intelligence model and its in-progress implementation to direct users toward an optimal usage of their home appliances as a way of getting both personal advantage and an overall reduction of pollution and energy consumption. In this model sustainability is considered with respect to two types of resources: natura...
Article
Full-text available
Three Business case studies in University Laboratories on learning and mobility allow experimenting new multidisciplinary expertise, multimedia data management, analysis, distributed collaboration. Software and Hardware engineering practices, cloud technology-based, benefit from prototyping, in satisfying the needs of customers, validation of prici...
Article
In this paper we instantiate a learning by gossip paradigm to ful�ll an occupancy detection task via a minimum value proposition. Minimality is achieved by both the hardware and the data infrastructure, as well as by the data collection that is necessary to tune the occupancy detection intelligence. For short, we implement a loose scheme of edge co...
Article
Full-text available
We start from the very operational perspective – having data, organize them in a suitable way to be used in the future – to enter the long standing fray on the nature of inferred parameters within a machine learning thread. Still in an operational perspective, we introduce a parametric inference approach that unprecedentedly gets rid of most drawba...
Article
Full-text available
In the context of complex granule computations within the Interactive Granular Computating (IGC) paradigm we frame a cognitive task where user perceptions of the suitability of a good are in relation to the parameters of the device producing it, all within a learning loop aimed at continuously improving those perceptions. We achieve this goal by ex...
Chapter
Full-text available
We introduce a new recommending paradigm based on the genomic features of the candidate objects. The system is based on the tree structure of the object metadata which we convert in acceptance rules, leaving the user the discretion of selecting the most convincing rules for her/his scope. We framed the deriving recommendation system on a content ma...
Chapter
We extend the Fuzzy Inference System (FIS) paradigm to the case where the universe of discourse is hidden to the learning algorithm. Hence the training set is constituted by a set of fuzzy attributes in whose correspondence some consequents are observed. The scenario is further complicated by the fact that the outputs are evaluated exactly in terms...
Article
Full-text available
People intentionality within social network community may be seen as a further physical feature of those agents. In this perspective we study the Hamiltonian of a set of particles having a cognitive potential field in addition to the physical ones related to their mass and velocity, in a force field where masses and strengths have a cognitive value...
Article
Full-text available
We introduce a peculiar ecosystem aimed at ruling in remote the household appliances of the members of a special social network. The keen feature of the social network is a networked intelligence, equipped with cognitive tools that enable it to provide services fully compliant with the members' needs. The scheme is the following: The appliances are...
Article
Trust prediction in Social Networks is required to solve the cold start problem, which consists of guessing a Trust value when the truster has no direct previous experience on the trustee. Trust prediction can be achieved by the application of machine learning approaches applied to reputation features, which are extracted from the available Trust i...
Article
Subconscious Social Intelligence refers to the design of social services oriented towards user problem solving, providing an underlying innovation layer able to generate new solutions to yet unknown problems. The innovation layer is achieved by Computational Intelligence techniques, encompassing machine learning to build models of user satisfaction...
Conference Paper
We instantiate a social things paradigm in terms of a social network of facts which drives our household appliances in our name. The appliances are connected to the network, directly receiving the sequence of instructions (parameter/value pairs) constituting the recipe to perform a task requested by the user. The recipes are issued by the computati...
Research
Full-text available
In this paper we propose a family of methods for computing confidence regions for the parameters of a multinomial random variable based on the Algorithmic Inference approach. The novelty of our approach lies in a revisitation of the fiducial intervals introduced by Fisher that is based on a clear way of computing the parameters’ distribution law. T...
Conference Paper
In this paper we introduce a platform tailored to give teachers and trainers appropriate knowledge, skills, and innovative tools in the domain of the entrepreneurial education. To this end, a social network is created where teachers can formally or informally share experiences supporting their peers with technical training, along with theory and pr...
Chapter
This paper introduces principal ideas of new ways to mediate the interaction between users and their domestic environment, namely the set of household appliances owned by the user. These ideas are being developed in the framework of the Social and Smart (SandS) project, which elaborates on the idea of a social network of home appliance users that e...
Article
With the ambition of providing teachers with a concrete tool for worldwide exploiting didactic contents to feature their courses, we face the problem of creating a social platform with adequate functionalities to satisfy the teacher expectations. Starting with a well designed architecture we endow it with three key functionalities that become the s...
Article
We describe a diffuse control system for household appliances rooted in an Internet of Thing network empowered by a cognitive system. The key idea is that these appliances constitute an ecosystem populated by a plenty of devices with common features, yet called to satisfy in an almost repetitive way needs that may be very diversified, depending on...
Article
Full-text available
This paper discusses a statistical analysis emerging in the field entrepreneurship education, as a result of a survey conducted in the frame of the European Project NETT (Networked Entrepreneurship Training of Teachers, http://nett-project.eu). The analysis concerns both the quality of data and the emergence of some special patterns denoting some i...
Conference Paper
In the last 25 years many works in literature about the capability to detect or predict the occurrence of epileptic seizures, starting from the electroencephalogram (EEG) signal analysis, have often hypothesized that the epileptogenic activity is the result of an abnormal electrical activity hypersynchronization of different points in an epileptic...
Conference Paper
The Social and Smart (SandS) project aims to lay the foundations for a social network of home appliance users endowed with a layer of intelligent systems that must be able to produce new solutions to new problems on the basis of the knowledge accumulated by the social network players. The system is not a simple recollection of tested appliance use...
Conference Paper
A social network of eahoukers is intended to benefit from the socially generated knowledge to deal with the home appliances in a domestic environment. The entire system being developed in the SandS project has diverse facets, in this paper we focus on a discussion of the trust requirements from several points of view. Trust has been studied for a l...
Article
Full-text available
We cope with the key step of bootstrap methods of generating a possibly infinite sequence of random data preserving properties of the distribution law, starting from a primary sample actually drawn from this distribution. We solve this task in a cooperative way within a community of generators where each improves its performance from the analysis o...
Conference Paper
Full-text available
I propose a three-step discussion following a research path shared in part with John Taylor where the leitmotif is to understand the cooperation between thinking agents: the pRAM architecture, the butler paradigm, and the networked intelligence. All three steps comprise keystones of European projects which one of us has coordinated. The principled...
Conference Paper
At a time when socialism as an economic option is variously questioned, very few people are against social instances of our life such as entertainment, customer assistance, and so on. This happens with the management of many things accompanying our life as well. We can find both the reason and the evidence for the viability of this trend in one ver...
Article
The Publisher regrets that this article is an accidental duplication of an article that has already been published, http://dx.doi.org/10.1016/j.neunet.2013.03.008. The duplicate article has therefore been withdrawn.
Article
We revise the notion of confidence with which we estimate the parameters of a given distribution law in terms of their compatibility with the sample we have observed. This is a recent perspective that allows us to get a more intuitive feeling of the crucial concept of the confidence interval in parametric inference together with quick tools for exa...
Conference Paper
Three Business case studies in University Laboratories on learning and mobility allow experimenting new multidisciplinary expertise, multimedia data management, analysis, distributed collaboration. Software and Hardware engineering practices, cloud technology-based, benefit from information acquired from the Web, increasing abilities in rapid proto...
Article
Full-text available
The aim of this Special Issue is to solicit theoretical and application-oriented research in the field of neural computing and to present examples of experimental and real-world investigations that demonstrate the advances, successes, and state-of-the-art of the developments in the neural computing area. We believe it provides a good opportunity fo...
Article
Full-text available
We introduce a wait-and-chase scheme that models the contact times between moving agents within a connectionist construct. The idea that elementary processors move within a network to get a proper position is borne out both by biological neurons in the brain morphogenesis and by agents within social networks. From the former, we take inspiration to...
Conference Paper
We introduce a morphogenesis paradigm for a neural network where neurons are allowed to move au- tonomously in a topological space to reach suitable reciprocal positions under an informative perspective. To this end, a neuron is attracted by the mates which are most informative and repelled by those which are most similar to it. We manage the neuro...
Conference Paper
Full-text available
We introduce a new paradigm of neural networks where neurons autonomously search for the best reciprocal position in a topological space so as to exchange information more profitably. The idea that elementary processors move within a network to get a proper position is borne out by biological neurons in brain morphogenesis. The basic rule we state...
Conference Paper
Full-text available
We add a mobility functionality to the neurons of an artificial neural network as a key expression of their intentionality of cooperating in the overall computational task of the network. We draw the main features of this functionality from mobility models developed in some macroscale biological frameworks. The goal is to improve the learning capab...
Article
Full-text available
Two Business case studies in University Laboratories on learning and mobility present the opportunity to experiment new multimedia data management, data analysis, distributed collaboration. Software engineering practices based on cloud technology techniques acquire from the Web what is needed for rapid prototyping, capability of satisfying the need...
Article
We propose a variant of two SVM regression algorithms expressly tailored in order to exploit additional information summarizing the relevance of each data item, as a measure of its relative importance w.r.t. the remaining examples. These variants, enclosing the original formulations when all data items have the same relevance, are preliminary teste...
Conference Paper
Full-text available
We describe a wireless platform for implementing domotic applications drawn from a fuzzy rule system. The design of its architecture hits three targets: i) complete scalability with the addition of new devices into the domotic system, ii) full operability by the user who is the arbiter of any operational option, and iii) robotic controllability bas...
Article
Full-text available
We deal with a special class of games against nature which correspond to subsymbolic learning problems where we know a local descent direction in the error landscape but not the amount gained at each step of the learning procedure. Namely, Alice and Bob play a game where the probability of victory grows monotonically by unknown amounts with the res...
Conference Paper
Full-text available
Within the framework of Algorithmic Inference, we recall a linear regression analysis tool based on the identification of the joint probability distribution of the regression coefficients compatible with the sampled data and aimed at finding out the independent components of this distribution. On this distribution we implement specific Independent...
Article
Full-text available
We discuss a bridge way of inference between Agnostic Learning and Prior Knowledge based on an inference goal represented not by the attainment of truth but simply by a suitable organization of the knowledge we have accumulated on the observed data. In a framework where this knowledge is not definite, we smear it across a series of possible models...
Article
Full-text available
We devise a feature selection method in terms of a follow-out utility of a special classification procedure. In turn, we root the latter on binary features which we extract from the input patterns with a wrapper method. The whole contrivance results in a procedure that is progressive in two respects. As for features, first we compute a very essenti...
Article
Full-text available
We provide an estimation procedure of the two-parameter Gamma distribution based on the Algorithmic Inference approach. As a key feature of this approach, we compute the joint probability distribution of these parameters without assuming any prior. To this end, we propose a numerical algorithm which is often beneficial of a highly efficient speed u...
Conference Paper
Full-text available
We solve the manufacturing problem of identifying the model statistical parameters ensuring a satisfactory quality of analog circuits produced in a photolithographic process. We formalize it in a statistical framework as the problem of inverting the mapping from the population of the circuit production variables to the performances’ population. Bot...
Conference Paper
Full-text available
The paper introduces a π-calculus simulator devoted to reproducing some local coherence phenomena that occur in the somato-sensory thalamic and cortical stations of experimental animal models of chronic pain. On the one hand, neuronal signals are registered in an experimental setup by extracellular electrode arrays placed in the two regions of the...
Conference Paper
Full-text available
We present a sensitivity study of a wait and chase scheme introduced in a previous work to model the contact times between people belonging to a social community. The membership presupposes that, besides purely occasional encounters, people are motivated to meet other members of the community, while the social character of the latter makes each per...
Chapter
Full-text available
Consider a web society comprised by a huge number of agents communicating with one another. Each agent enjoys a wide facility in receiving and sending data and a very small capacity for processing them. Hence data constitute a heap of microgranules of information. Each individual processes data by him- or herself with the sole goal of increasing pe...
Chapter
There is no doubt that the sharing of information lies at the basis of any collaborative framework. While this is the keen contrivance of social computation paradigms such as ant colonies and neural networks, it also represented the Achilles’ heel of many parallel computation protocols of the eighties. In addition to computational overhead due to t...
Article
Full-text available
Leaving the expert systems framework of the 80s and the early connectionist paradigm of the 90s, the scientific community is now drawn by social computing paradigms, where a huge number of agents individually do an elementary job and jointly give rise to a sophisticated functionality. There is no doubt that the complexity of this functionality is c...
Conference Paper
We analyze the potentialities of an approach to represent general data records through Boolean vectors in the philosophy of ICA. We envisage these vectors at an intermediate step of a clustering procedure aimed at taking decisions from data. With a “divide et conquer” strategy we first look for a suitable representation of the data and then assign...
Article
Full-text available
We introduce a regression method that fully exploits both global and local information about a set of points in search of a suitable function explaining their mutual relationships. The points are assumed to form a repository of information granules. At a global level, statistical methods discriminate between regular points and outliers. Then the lo...
Article
To get a true hybrid framework for taking operational decisions from data, we extend the Algorithmic Inference approach to the Granular Computing paradigm. The key idea is that whether or not we need to make decisions instead of mere computations depends on the fact that collected data are not sufficiently definite; rather, they are representative...
Article
Full-text available
We formulate a new family of bootstrap algorithms suitable for learning non-Boolean functions from data. Within the Algorithmic Inference framework, the key idea is to consider a population of functions that are compatible with the observed sample. We generate items of this population from standard random seeds and reverse seed probabilities on the...
Conference Paper
In view of discussing the genuine roots of the connectionist paradigm we toss in this paper the non symmetry features of the involved random phenomena. Reading these features in terms of intentionality with which we drive a learning process far from a simple random walk, we focus on elementary processes where trajectories cannot be decomposed as th...
Article
A traditional way of introducing the inference facility in operational contexts is through the match box metaphor. You buy your box and wonder how many matches will fire, how many not. You cannot check all them otherwise you will be satisfied with your knowledge but cannot use the obtained information on the current box because it became empty. Thu...
Article
In Chapters 6 and 8 we discussed separately symbolic rules for identifying membership functions to cluster and subsymbolic rules to learn functions that suitably translate a set of inputs into an output variable. Here we look for complete procedures performing both tasks having the final aim of computing suitable functions from input to output. The...