NCube/papyrus huggingface dataset:
La personne selon Paul Ricoeur : une institution narrative

Paul Ricoeur’s philosophy is essentially focused around one subject, the subject by excellence : the human being. Through his approach, greatly inspired by phenomenology and hermeneutics, Ricoeur proposes conciliatory solutions to dialectics that oppose each other. To the human concepts of « Volontaire » (voluntary) and « Involontaire » (involuntary), he thinks the person. In regards to phenomenological and cosmological time, he defends the notion of a human time. Finally, to the two forms of personal identity, Idem et Ipse, he proposes the theory of narrative identity as a unifying principle. This theory is the center of gravity of all his philosophy and its role within the debate concerning personal identity has taken considerable importance over the last few decades. The object of this research memoir is thus to analyze, explicit, and understand Paul Ricoeur’s theory of narrative identity. To do so, we notably explain it with the help of Parfit’s lexicology, terms such as reductionnism, non-reductionnism, and the further fact. In fact, we domonstrate  that the further fact, within the narrativist theory, is the semiotic subject, the “I” of language. Furthermore, from this linguistic subject, we analyze the distinction between the two interpretative frames of personal identity : naturalism and non-naturalism. We conclude that Ricoeur observes the person through an institutionnalist frame, which allows us to assert that the person, in the french philosopher’s eyes, is a narrative institution. Finally, we finish this research by presenting the ontological foundations of the narrative identity theory, which revolve around two principal axes : dynamism and dualism. Thus, we explain these principles with the help of the general process theory (GPT) and the three world’s theory. Overall, the objective of this memoir is to present, in a very detailed manner, in what consists Paul Ricoeur’s narrative identity theory, on what ontological foundation it rests and through which interpretative frame does it explain what is a person.

Keyphrases: Idem, Ipse, Philosophy, Personal identity, Narrativism, Reductionnism, Non-reductionnism, Further fact, Semiotic subject, Language, Time, Naturalism, Ontology, Process, Dualism, Existentialism, Hermeneutics, Phenomenology
L'institution policière et la notion d'égale protection du citoyen

Starting from the political thought stemming from the liberal tradition (more specifically that of John Rawls and his conception of justice as equity), we will try to circumscribe the problematic posed by the institutional justification of normative principles resulting from illegitimate conceptions of authority in the context of police action, within contemporary liberal societies. Based on an analysis of the notion of legitimate authority held by the institutions in a state of law, we want to understand, in this work, how and why a lack of adequate reflexive practices in the field of normative ethics can lead public protection agencies to conflict with the function assigned to them by the institution they represent, as well as some of the fundamental principles underlying the structure of today's liberal societies.

Keyphrases: institution policière, philosophy, police institution, liberalism, democracy, authority, normative ethics
Les limites de l'homo oeconomicus par l’analyse du Black Friday : puissance, dépense et rituel de masse

The aim of this research is to understand the Black Friday’s foundation as a means to determine if it serves a social function. Two subquestions will orient our research. First of all: What does the Black Friday teach us about human nature? Then: How to explain its establishment in the American culture? From Thomas Hobbes’s anthropology, the Black Friday will at first be looked at from an utilitarian conception of human nature and social relations. Humanity will hence be considered in terms of homo oeconomicus. The economical analysis will be rapidly confronted to limitations and will then be contested by the symbolic exchange hypothesis. By examining Marcel Mauss’s studies on the gift, we will consider human experience from these symbolic rapports to the world. It could therefore be speculated that the Black Friday is a social ritual where the gift maintains human bonds as well as social hierarchy. Our examination will be completed by an accurate comprehension of the context that allows the emergence of this ritual. Jean Baudrillard will grant the understanding of consumer society’s specificities and how this context is thought of as a religious system. Confronted to the limits of this interpretation, we will accept that the ritual’s essence could be distorted. This view will authorize a critical attitude pertaining to the Black Friday.

Keyphrases: Black Friday, Instrumental rationality, Individualism, Competition, Power, Ritual, Gift, Expenditure, Symbolism, Consumption
La théorie de la représentation de l'algèbre de Temperley-Lieb

The goal of this Master’s thesis is to study the representation theory of the one boundary Temperley-LiebalgebrasTLbn(β,β1,β2),whereβ1,β2 ∈Candβ=q+q−1 withq∈C∗. These are unitary associative algebras of finite dimensions which generalize the more familiar regular Temperley-Lieb algebras TLn(β). Our aim is to classify their irreducible and principal representations. For generic values of the parameters, TLbn is semisimple. However, for certain specializations of the parameters q,β1,β2, the algebra is not semisimple and in that case, the irreducible, principal and cellular representations are distinct in general. In chapter 1 it is shown that TLbn(β,β1,β2) admits a diagramatic presentation which is isomorphic to the formulation in terms of generators and relations. In chapter 2, it is shown that the one boundary Temperley-Lieb algebras are cellular algebras and the associated cell modules are computed. An invariant bilinear form is defined on the cell modules. Chapters 3 and 4 study the radicals of the cell modules, leading to the identification of the irreducible and principal modules for any β1,β2 ∈ C and generic q. In particular, the β2 = 0 case is included in our analysis.

Keyphrases: One boundary Temperley-Lieb algebra, Blob algebra, Cellular algebras, Cell modules, Principal modules (projective indecomposable modules), Gram matrices, Representation theory of associative algebras
Partition adaptative de l’espace dans un algorithme MCMC avec adaptation régionale

Sampling from multimodal distributions using MCMC methods is an ongoing challenge. Most adaptive algorithms aim to find a good compromise between asymptotic efficiency and actual computation time. In this masters thesis, we propose an improvement to the regional adaptive(RAPT) MCMC algorithm of Craiu et al. (2009), that consists in adding a constrained adaptive partitionning of the sample space. Precisely, the adaptive partition is defined as the hyperplane that is orthogonal to the line joining the cumulative sample means in each region, and which passes through the equidistant point between those two means, according to the Mahalanobis distance. We thus obtain an algorithm that is robust to the choice of the initial partition, at a mimimal computational cost.   The workings of the algorithm and its variants are detailed and set in the general framework of adaptive MCMC.  A review of some widely used regional adaptation algorithms is also included. The ergodicity of the generated sampler is proved using the sufficient ergodicity conditions of Roberts et Rosenthal (2007).   Graphical illustrations of the adaptive partitionning are presented. Our approach is then compared to the RAPT and RAPTOR algorithms through many examples inspired by MCMC litterature. Our new algorithm yields satisfactory results and is in some cases the best choice among those considered, especially when taking into account the computational effort.

Keyphrases: MCMC, Partition, Distributions bimodales, Adaptive algorithms, Regional adaptation, Partitionning, Ergodicity, Bimodal distributions
Sequence to sequence learning and its speech applications

Recurrent Neural Networks (RNNs), which has the attractive properties of modelling sequences, has been dominant in speech field in the recent decades. Convolutional Neural Networks (CNNs) has been shown as an alternative to model sequences because of its capacity of reducing spectral variations and modeling spectral correlations in acoustic features for automatic speech recognition (ASR). Recent work suggests that complex numbers could be used as a richer feature representation than spectrum which may benefit the speech related tasks. In the thesis, we first cover the basic concepts in machine learning, building blocks of deep learning and discuss the popular methods that are capable of doing sequence-to-sequence modelling, specially convolutional neural networks, which is famous as a class of feed-forward nets. We then present two research work related to sequence-to-sequence modelling on speech. We introduce a new approach to address speech recognition with convolutional neural networks which shows the comparable results with their recurrent neural networks counterpart. In addition, we present a new model taking advantage of the representation in the complex domain and define complex convolutions, complex batch-normalization, complex weight initialization strategies. The new model results in state-of-the-art of speech spectrum prediction in a convolutional recurrent setting.

Keyphrases: Neural networks, Machine learning, Deep learning, Convolutional neural networks, Sequence modelling, Speech recognition, Complex representation
Predictive models for career progression

LinkedIn is the largest social network for professionals where users of the service share all of their professional history. In this work we explore methods by which we can model the career trajectory of a given candidate and predict future career moves. The first part of this thesis is an attempt to normalize the job titles data as we have found that there is a great deal of variation in how the users of the professional social networking platform decide to input their titles. Then we move on to exploring various predictive models inspired form language models as well as sequential neuronal models.

Keyphrases: LSTM, Data mining, Naive bayes, Sequence labeling, Sequence classification, Neural networks, Recurrent neural networks
Using electroencephalograms to interpret and monitor the emotions

The long journey of technology has totally changed human’s life: human stepped on the moon, Mars rovers2 are discovering the Mars, computers are one inseparable part of our lives and in the health section, people live longer, there are treatments for lots of sicknesses. Also, scientists have studied human’s emotion and tried to detect their emotions based on different parameters such as facial expression, speech and intonation, electrical response, verbal communication. These methods work based on the effect of human emotions on body and behavior, but the emotion is not the only parameter that effect on body and attitudes of people. Additionally, people could pretend, hide their emotions and control their body and reactions, also, people with a limit on their body movement will reduce the accuracy of correct recognition of emotion. Researchers found a direct relation between emotions and brain activities, people or limit in body movement could not reduce the certainty of detected emotion.  We used EEG (Electroencephalogram) to create a tool called Emotimap that detects current emotion, monitor emotional evolution in real-time, also detects the general emotion. Current emotion is brief and strong, emotions that people feel again any emotional factor and general emotion is the emotion that engages people for a long time. Emotimap uses formulas to calculate the Arousal and Valence of people then ignore unstabled feels and maps the result on the two dimensions Russel’s Circumplex diagram to detect the emotions.  We asked 20 people to participate in an experimentation in which they faced up with different emotional factors in an isolated Virtual Reality (VR) to observe and save the information of emotional factor and their reactions. The results show participants have felt exactly what was expected with the rate of 37.73% when the metric distance is just 1.55%, metric distance is the proximity of felt and expected emotions (smaller number shows the more similarity). Comparing different formulas shows the most similar equations goes to formulas with the same number of sensors using 𝛽 and 𝛽low with the rate of 40% of similarity, with metric distance in range of 20% to 60%. This is because some equations detect emotions sooner and some others are more strong in picks amplitude. In detaile, equation with 𝛽high detects an emotion a little bit sooner then a equation with 𝛽low, also, formulas with twelve sensors chase the EEG amplitude changes very weak when equation with four sensors are more sensible in picks, and the formulas with two sensors are the most sensible. Comparing the similarity of the participant reactions with their similarity of charactristics based on Big 5 test shows that the effect of memories is more stronger than the effect of their charactristic. Analysing the result shows Emotionap could successfully detect general emotion of participant with the rate of 95%.

Keyphrases: AI, Emotion, EEG, VR, IA, RV
Le produit direct de fonctions et les programmes de branchement avec oracle

This dissertation explores various results from the literature about the direct product of functions. We discuss mass production, multi-computation and catalytic space. We ex- plicitely show for the first time the link these three variants of the direct product of func- tions. Mass production allows economy of resources during the computation of a function on multiple inputs. We present a bound on the size of circuits which compute a function a super-polynomial number of times. With multi-computation, we can represent sharing of resources when computing multiple functions over the same input. The last one, cat- alytic space, is the intersection of mass production and multi-computation. A computation in catalytic space is computing a function multiple times over the same input. We study the catalytic space with Turing machines whose part of their memory needs to be restore to its initial content. We present in detail the result from the literature which shows the inclusion of TC 1 in the logarithmic catalytic space. In the second section, we contribute with a new family of branching programs. We then derive parametric languages. We prove that one of them is coNP-complete.

Keyphrases: Complexity theory, Branching program, Catalytic space, Mass production
Generative models : a critical review

In this thesis we introduce and motivate generative modeling as a central task for machine learning and provide a critical view of the algorithms which have been proposed for solving this task. We overview how generative modeling can be de ned mathematically as trying to make an estimating distribution the same as an unknown ground truth distribution. This can then be quanti ed in terms of the value of a statistical divergence between the two distributions. We outline the maximum likelihood approach and how it can be interpreted as minimizing KL-divergence. We explore a number of approaches in the maximum likelihood family, while discussing their limitations. Finally, we explore the alternative adversarial approach which involves studying the di erences between an estimating distribution and a real data distribution. We discuss how this approach can give rise to new divergences and methods that are necessary to make adversarial learning successful. We also discuss new evaluation metrics which are required by the adversarial approach. Chapter 2 shows that by learning generative models of the hidden layers of a deep network can identify when the network is being run on data di ering from the data seen during training. This allows us to study di erences between freerunning and teacher forcing modes in recurrent networks. It also leads to improved robustness to adversarial attacks. Chapter 3 explored an iterative procedure for generation and inference in deep networks, which is inspired by the blocked gibbs MCMC procedure for sampling from energy-based models. This achieves improved inpainting, generation, and inference by removing the requirement that the prior over the latent variables have a known distribution. Chapter 4 studied whether generative models could be improved by exploiting the knowledge learned by discriminative classi cation models. We studied this by augmenting autoencoders with additional losses de ned in the hidden states of a  xed classi er. In practice we showed that this led to generative models with better focus on salient aspects of the data, and also discussed limitations in this approach.

Keyphrases: Neural networks, Machine learning, Deep learning, Supervised learning, Generative modeling, Structured prediction
Détection des utilisations à risque d’API : approche basée sur le système immunitaire

APIs are essential ingredients for developing complex software systems. However, they are difficult to learn and use. As a result, developers can misuse them, resulting in different types of issues. Misuse of a programming interface can lead to errors that are very difficult to detect and can have consequences. Detecting these misuses is not easy. We have thus developed an approach based on the immune system, a mechanism that allows to detect known and unknown anomaly types. Here the cells of the organism will be the good uses of the API and the bad ones will be the foreign cells of the organism. The immune system has the particularity of being a decentralized system that functions thanks to detectors, T lymphocytes, whose role is to detect foreign cells. With APImmune we will therefore generate detectors that have the ability to detect risky uses of APIs. Our approach was evaluated on two sets of data and more specifically MUBench. The results show that our approach complements previous works in this area of research. In addition, the detectors can be generated from source code by abstracting the API usages and by generating artificial deviations from these usages. Moreover, for the detection purpose, only the artificial detectors are necessary, and the code used to generate them is not disclosed. Finally, the detectors can be produced for different versions of the programming interface, that brings modularity in the detection.

Keyphrases: API, API Misuses, Programming interface, Artificial immune-system, Software engineering
La fiction à la première personne en réalité virtuelle

It is rare to design a whole movie from the point of view of a character and based solely on subjective camera. The first-person perspective does not elicit identification the way the objective perspective does as the latter allows us to see the character and his/her facial expression and gestuality. However, with the advent of virtual reality’s immersive apparatuses, this practice has resurfaced. Could it be an indication of the development of a new technical, narrative, and aesthetic approach? Could we base the construction of a fiction on the sensori-motor experimentation in the first person? Would it lead to a deeper empathic understanding of the character? Our thesis studies this principal question in two ways: in a written text, that examines the history and the theory; in the making of a short 360 degrees fiction film in the first person, which allowed us to explore this medium’s resources and better understand the challenges related to its use.

Keyphrases: Identification, Virtual reality, Narrative, Sensori-motor stimuli
La construction des artistes femmes du Moyen-Orient dans les expocollections du Centre Pompidou : les cas de "elles@centrepompidou" et "Modernités plurielles de 1905 à 1970"

This master’s thesis focuses on understanding the way thematic exhibitions can influence the initial meaning of art works from collections, often left dormant in the museum's reserves. In order to make my case, I will use as examples two recent exhibitions based on the collections of the Musée national d'art moderne du Centre national d'art et de culture Georges-Pompidou: elles@centrepompidou and Modernités plurielles de 1905 à 1970, presented respectively in 2009 and 2013. While the first one aimed to show the breadth of the representation of women artists within the institution's collection, the second considered the collections within the new paradigm of global art. In each exhibition, I have identified the art works created by Middle Eastern female in order to analyze the place devoted to them, and if and how their works were instrumentalized in the light of each theme. I will also seek to understand how these exhibitions propose a certain vision of the modern and contemporary practices of women artists from the Middle East within a leading art institution of the Western art world. The first two chapters are dedicated to an in-depth description and analysis of each exhibition; in the third and last chapter I propose a comparative argument grounded on the observations raised in the first two chapters and the broader issues they suggest. In addition to bibliographic research on the exhibitions displays, I proceed through a study of press releases, press reviews and exhibition catalogues that accompany the exhibitions studied. A research journey to Paris was carried out in September 2017 in order to have access to the archives of the Centre national d'art et de culture Georges-Pompidou, in particular to the iconographic file of the views of these exhibitions. Our theoretical framework focuses on museum, feminist and postcolonial studies. I will favour a museum approach specific to the field of exhibition (Mieke Bal 1996, Jérôme Glicenstein 2009) by limiting ourselves to exhibitions promoting a permanent collection and we will adopt a constructivist feminist perspective (Rozsika Parker and Griselda Pollock 1981).

Keyphrases: Modern and contemporary art, Museum collections, Exhibition, Women artists, Middle East
Le cinéma entre les cultures : enjeux, analyses et créations

Media technologies and international mobility have rendered a century where we are continuously exposed to other cultures. In the cinematic world - that of images, narratives, sounds, music, faces, lighting, editing - this interaction between cultures has been explored before through the use of traditional cinema. Today, new audiovisual technologies, the use of data networks and the capacity to reach audiences on a global scale have taken this intercultural interaction to new, fluid, dynamic, and portable levels. However, the role of cinema in understanding interculturality has not been sufficiently explored. On this theses, I use a new perspective based on the notion of interité culturelle (Demorgon) to further engage the conceptual apparatus used by film studies. I will analyze four films to understand the basics of interculturality on the screen, during the production of the film, and in rapport to the viewer. To do this, I will use two concepts: faces (visages) and intimacy (intimité). They will enable us to approach cinema as a process of encounters and survival, both cultural and biological, of narrated communities. Interculturality invests in the medium of cinema to express itself and share codes - social, moral, historic, discursive, to name a few- between different communities. In a world and a time fascinated by once-cinematic technologies, individuals now create and consume images, sounds and narratives as they participate, consciously or not, in the dynamic definition of their own culture and that of others. To illustrate this and understand the dimensions of today’s cinematic interculturality, I analyze four films: Mommy (2015), Tangerine (2015), Human (2015), and Dheepan (2015). This theses also has a creative component presented in form of a screenplay called Mobilité.

Keyphrases: Intimité, Imagination, Postcinematic condition, Imaginaires, Visage, Interculturality, Intimacy, Identity, Positionalities, Faces