NCube/papyrus huggingface dataset:
Optimizing ANN Architectures using Mixed-Integer Programming

Over-parameterized networks, where the number of parameters surpass the number of train-ing samples, generalize well on various tasks. However, large networks are computationally expensive in terms of the training and inference time. Furthermore, the lottery ticket hy-pothesis states that a subnetwork of a randomly initialized network can achieve marginal loss after training on a specific task compared to the original network. Therefore, there is a need to optimize the inference and training time, and a potential for more compact neural architectures. We introduce a novel approach “Optimizing ANN Architectures using Mixed-Integer Programming” (OAMIP) to find these subnetworks by identifying critical neurons and re-moving non-critical ones, resulting in a faster inference time. The proposed OAMIP utilizes a Mixed-Integer Program (MIP) for assigning importance scores to each neuron in deep neural network architectures. Our MIP is guided by the impact on the main learning task of the net-work when simultaneously pruning subsets of neurons. In concrete, the optimization of the objective function drives the solver to minimize the number of neurons, to limit the network to critical neurons, i.e., with high importance score, that need to be kept for maintaining the overall accuracy of the trained neural network. Further, the proposed formulation generalizes the recently considered lottery ticket hypothesis by identifying multiple “lucky” subnetworks, resulting in optimized architectures, that not only perform well on a single dataset, but also generalize across multiple ones upon retraining of network weights. Finally, we present a scalable implementation of our method by decoupling the importance scores across layers using auxiliary networks and across di˙erent classes. We demonstrate the ability of OAMIP to prune neural networks with marginal loss in accuracy and generalizability on popular datasets and architectures.

Keyphrases: deep learning, Pruning Neural Networks, Mixed-Integer Programming, Neurons Ranking, Combinatorial optimization, Architecture Optimization
Study and experimentation of cognitive decline measurements in a virtual reality environment

At a time when digital technology has become an integral part of our daily lives, we can ask ourselves how our well-being is evolving. Highly immersive virtual reality allows the development of environments that promote relaxation and can improve the cognitive abilities and quality of life of many people. The first aim of this study is to reduce the negative emotions and improve the cognitive abilities of people suffering from subjective cognitive decline (SCD). To this end, we have developed a virtual reality environment called Savannah VR, where participants followed an avatar across a savannah. We recruited nineteen people with SCD to participate in the virtual savannah experience. The Emotiv Epoc headset captured their emotions for the entire virtual experience. The results show that immersion in the virtual savannah reduced the negative emotions of the participants and that the positive effects continued afterward. Participants also improved their cognitive performance. Confusion often occurs during learning when students do not understand new knowledge. It is a state that is also very present in people with dementia because of the decline in their cognitive abilities. Detecting and overcoming confusion could thus improve the well-being and cognitive performance of people with cognitive impairment. The second objective of this paper is, therefore, to develop a tool to detect confusion. We conducted two experiments and obtained a machine learning model based on brain signals to recognize four levels of confusion (90% accuracy). In addition, we created another model to recognize the cognitive function related to the confusion (82% accuracy).

Keyphrases: IA, Relaxation, Confusion, Dementia, AI, Machine learning, Alzheimer’s disease, Virtual reality therapy, Emotions, EEG signals, Subjective cognitive decline, Relaxation, Confusion
Programming tools for intelligent systems

Programming tools are computer programs which help humans program computers. Tools come in all shapes and forms, from editors and compilers to debuggers and profilers. Each of these tools facilitates a core task in the programming workflow which consumes cognitive resources when performed manually. In this thesis, we explore several tools that facilitate the process of building intelligent systems, and which reduce the cognitive effort required to design, develop, test and deploy intelligent software systems. First, we introduce an integrated development environment (IDE) for programming Robot Operating System (ROS) applications, called Hatchery (Chapter 2). Second, we describe Kotlin∇, a language and type system for differentiable programming, an emerging paradigm in machine learning (Chapter 3). Third, we propose a new algorithm for automatically testing differentiable programs, drawing inspiration from techniques in adversarial and metamorphic testing (Chapter 4), and demonstrate its empirical efficiency in the regression setting. Fourth, we explore a container infrastructure based on Docker, which enables reproducible deployment of ROS applications on the Duckietown platform (Chapter 5). Finally, we reflect on the current state of programming tools for these applications and speculate what intelligent systems programming might look like in the future (Chapter 6).

Keyphrases: Kotlin, Docker, Software engineering, Machine learning, Applied mathematics, Programming languages, Programming tools, Type systems, Automatic differentiation, Automated testing, Embedded systems, Intelligent systems, Virtual machines, ROS, Metamorphic testing, Differentiable programming, Probabilistic programming, Functional programming, Compilers, Generative modeling, Rétropropagation, Backpropagation, Fuzzing, Metamorphic testing, Property-based testing, Static analysis, Build automation, Continuous integration
Edit distance metrics for measuring dissimilarity between labeled gene trees

Phylogenetic trees are instruments of evolutionary biology offering great insight for comparative genomics. They provide mechanisms to model the kinship relations between species or members of gene families as a function of taxonomic diversity. They also provide evidence and insights into the evolutionary history, structure, and variation of biological processes. However, traditional phylogenetic inference methods have the reputation to be prone to errors. Therefore, comparing and analysing phylogenetic trees is indispensable for obtaining the best interpretation of the biological information they can provide. We start by assessing existing related work to infer, compare, and analyse phylogenetic trees, evaluating their advantageous traits and flaws, and discussing avenues for future improvements. The second part of this thesis focuses on the development of efficient and accurate metrics to analyse and compare pairs of gene trees with labeled internal nodes. We show that our attempt in extending the popular Robinson-Foulds metric is useful for the preliminary analysis and comparison of labeled gene trees under various evolutionary models that may involve various evolutionary events.

Keyphrases: Robinson-Foulds, Evolution, Edit distance, Gene tree, Labeled tree, Tree metric, Evolutionary history
Personal information prediction from written texts

Authorship Attribution (AA) is a field of research that exists since the 60s. It consists of identifying the author of a certain text based on texts with known authors. This is done by extracting features about the writing style and the content of the text. In this master thesis, two sub problems of AA were treated: gender and age classification using a corpus collected from online blogs. In this work, several features were compared using several feature-based algorithms. As well as deep learning methods. For the gender classification task, the best results are the ones obtained by a majority vote system over the outputs of several classifiers. For the age classification task, the best result was obtained using classifier trained over TFIDF.

Keyphrases: Authorship attribution, natural language processing, machine learning, deep learning, privacy
Open source quality control tool for translation memory using artificial intelligence

Translation Memory (TM) plays a decisive role during translation and is the go-to database for most language professionals. However, they are highly prone to noise, and additionally, there is no one specific source. There have been many significant efforts in cleaning the TM, especially for training a better Machine Translation system. In this thesis, we also try to clean the TM but with a broader goal of maintaining its overall quality and making it robust for internal use in institutions. We propose a two-step process, first clean an almost clean TM, i.e. noise removal and then detect texts translated from neural machine translation systems. For the noise removal task, we propose an architecture involving five approaches based on heuristics, feature engineering, and deep-learning and evaluate this task by both manual annotation and Machine Translation (MT). We report a notable gain of +1.08 BLEU score over a state-of-the-art, off-the-shelf TM cleaning system. We also propose a web-based tool “OSTI: An Open-Source Translation-memory Instrument” that automatically annotates the incorrect translations (including misaligned) for the institutions to maintain an error-free TM. Deep neural models tremendously improved MT systems, and these systems are translating an immense amount of text every day. The automatically translated text finds a way to TM, and storing these translation units in TM is not ideal. We propose a detection module under two settings: a monolingual task, in which the classifier only looks at the translation; and a bilingual task, in which the source text is also taken into consideration. We report a mean accuracy of around 85% in-domain and 75% out-of-domain for bilingual and 81% in-domain and 63% out-of-domain from monolingual tasks using deep-learning classifiers.

Keyphrases: Machine translation, Cleaning translation memory, Sentence alignment, Machine translation detection, Deep neural network, Classification model, Classification
Entity-centric representations in deep learning

Humans' incredible capacity to model the complexity of the physical world is possible because they cast this complexity as the composition of simpler entities and rules to process them. Extensive work in cognitive science indeed shows that human perception and reasoning ability is structured around objects. Motivated by this observation, a growing number of recent work focused on entity-centric approaches to learning representation and their potential to facilitate downstream tasks.  In the first contribution, we show how an entity-centric approach to learning a transition model allows us to extract meaningful visual entities and to learn transition rules that achieve better compositional generalization.  In the second contribution, we show how an entity-centric approach to generating graphs allows us to design a model for conditional graph generation that permits direct optimisation of the graph properties. We investigate the performance of our model in a prototype-based molecular graph generation task. In this task, called lead optimization in drug discovery, we wish to adjust a few physico-chemical properties of a molecule that has proven efficient in vitro in order to make a drug out of it.

Keyphrases: Representation learning, Unsupervised learning, Deep learning, Entity-centric representations, Objects, Graphs generation, Graph neural networks, Conditional generation, Drug discovery
La construction de l’identité canadienne à travers le paysage, le cas des timbres peints par Jean Paul Lemieux

The purpose of this thesis is to contextualize and analyse Visions du Canada, a series of twelve landscapes representing the country’s provinces and territories. Commissioned to Quebec painter Jean Paul Lemieux by the Canada Post Corporation in 1982, they are issued in 1984 as part of Canada Day, an annual series designed to highlight national pride and belonging on Canada Day. Created in a semi classic style, these varied, colourful, and serene-like landscapes display a united, equal and diverse image of Canada. However, the historical and political context in which they are produced reveals a more complex reality. Indeed, the failure of the 1980 referendum on sovereignty and the Quebecers’ dissatisfaction with the terms of the Constitution’s patriation in 1982 fuel the cultural divide between Quebec and the rest of Canada. In Visions du Canada nature creates the basis for national unity as envisioned by the federal government. By commissioning works designed for national dissemination to the Quebec painter, the government, through the Canada Post Corporation, thus blurs the dichotomy between Quebecer and Canadian identity. The stamp’s intrinsic functions then render this message accessible to all Canadians. Therefore, an analysis of Visions du Canada reveals a more nuanced and complex perception of the Canadian landscape. The questions that punctuate Lemieux’s career, such as the relationship between the human being and the universe and the anguish in front of modernization, also challenge the myths of coexistence with nature and northerness that sustain the country’s claim to unity.

Keyphrases: Jean Paul Lemieux, Visions du Canada, Postage stamp, Myth, National unity, Landscape
Le film hybride : la voie d’un 3e genre

This Master’s memoir focuses on the border issue between documentary and fiction genres and its conception as a cinematic space for encounters, which could constitute a 3rd genre in itself. Genre that we propose to name hybrid. What justifies the persistence of the attachment to a reductionist binary system? Why do films that mix documentary and fiction approaches often meet with disapproval or negation of their duality? How to think about hybridity? What are the possible positive criteria and models for its election as a genre? This dissertation aims to analyze a rich corpus of films in order to identify how hybridity is constituted and also how it is perceived, both by film historians and thinkers, as well as by the media and the public. This study seeks to analyze cinematographic works grouped under four emblematic types, namely the mockumentary, the docufition, the docudrama and the so-called hybrid film, in order to identify the specific characteristics of these categories and to propose a model of hybrid film as a genre, in constructive and positive way. The creative component of this dissertation consists of a presentation file of a hybrid film project entitled The Legend of Tarō.

Keyphrases: Fiction, Genre, Hybrid, Documentary, Belief system, Docudrama
Le passé imparfait et la persistance de la mémoire : Flash-backs, temporalités, et remémorations dans le narratif cinématographique

This research-creation project comprises two components; the short film entitled Persistence de la mémoire, and the written document section. These two enunciated segments explore the concept of the double and the concepts of time, memory and the flashback. Developed as an autopoietic research-creation pursuant to a “practice-based research” methodology, this research-creation seeks to answer the following questions: In a film, what narrative tools are used to convey emotions, and key moments to represent time and memory? This question is divided into two sub-questions, which are: 1. How does the flashback become a way to alter or revise the past? 2. Is the flashback a subjective point of view of the protagonist or the author?  Based on my research and my creative process, I wish to bring an epistemological reflection to this question by examining the uses, particularities and modalities of narrative tools in storytelling. The concept of the double emerges as a common thread through my research and in the creation portion, as well as in the instances and uses of temporality and the flashback.

Keyphrases: Mémoire, Memory, Temporality, Recollection, Research-creation
Survivance 101 : Community ou l’art de traverser la mutation du paysage télévisuel contemporain

During the 2000s, the American televisual landscape was deeply shaken by the arrival of the Internet. The quick growth of digital technologies and the emergence of new types of media forced a reluctant television industry to change; be that in production, creation or reception. This transition from a pre-digital to a digital form of television was particularly difficult for the National Broadcasting Company (NBC). In the midst of this defining moment in American television history came Community (NBC, 2009-2014; Yahoo!Screen, 2015), a sitcom that embodied and reflected the various transformations brought by the convergence of the Internet and television, as well as the consequences this confluence bore to that industry. From being broadcast on NBC’s Must-See TV lineup between 2009 and 2014 to then moving to Yahoo!’s online platform in 2015, Community’s journey in television revealed its multiple attempts at adapting to a media in mutation. Therefore, the inability of the series to survive an unstable television industry through both traditional and online means underlines the complexity pertaining to television’s transition to a digital era.

Keyphrases: Community, sitcom, NBC, Yahoo!Screen, Dan Harmon, television, intertextuality, postmodernism, reflexivity, TV production, reception, cult TV
L’évolution des représentations des crimes sexuels et du harcèlement sexuel dans les téléséries américaines de fiction post #Metoo.

The social movement #Metoo has changed the way people think about sexual harassment and sexual abuse issues. Indeed, in the fall of 2017, a wave of denunciations broke out in the public sphere and since, the boundaries of what is acceptable and what is not seem to have been redefined within several societies. Based on this societal observation, we thought we noticed a revival of the issues surrounding the social movement #Metoo in American fiction television series. This paper aims to illustrate and analyze the evolution of representations of sexual crimes and sexual harassment inspired by the #Metoo movement. Considering the key milestones of this movement, this study focuses on its impact on North American society. This study also looks at a sociological framework in order to observe the way social representations work and thus, better understand their impact on a given society. In addition, by comparing two television corpuses characterized by the before and the after #Metoo, this paper wishes to highlight the points of similarities and disparities between these two periods evocative of the upheaval of morals around this issue. A film analysis of an episode example complements this argument.

Keyphrases: #Metoo, #Metoo, television, representations, sex crimes
Un athéisme spirituel : temps et danse dans le cinéma de Béla Tarr

This master’s thesis focuses on the dance scenes from three films by the Hungarian director Béla Tarr, in order to flesh out an aesthetic of time. The films’ analysis will be preceded by a research on the philosophy of time, centered around Paul Ricœur’s work Time and Narrative, in which the human time is described as a narrated time. Tracing his thought, we will define the notion of eternity as conceived by Augustine that is inseparable from a spiritual experience. We will then examine different issues of the history of dance in cinema concerning narrative, attraction and spirituality. This preliminary research will let us articulate our analysis between philosophy and aesthetic in order to describe a temporality expressed both intellectually in the films and lived by the viewer. Dance, while constructing a time of immanence that opposes the narrative regime, invites contemplation and opens an experience that is compatible with the Augustinian conception of eternity.

Keyphrases: Béla Tarr, contemplation, attraction, time, dance, eternity, spirituality
De série monde à série phénomène : analyse diégétique et de la réception de Xena la guerrière (1995-2001)

This dissertation proposes an analysis of a series phenomenon through the concept of world series developed in television and film. Our object of analysis is Xena: Warrior Princess (Syndication 1995-2001), a television series from the 1990s known in the contemporary era for the phenomenon of fandom created around the series and characters Xena and Gabrielle. The series of the late 1990s are part of an era of transition, where digital and narratives mutations come together in the creation of dense and complex objects. We will try to draw a parallel between the structure of a television series and its reception, both of which are based on a logic of densification, to be observed in different forms: extension, continuity, and derivation, as well as on two levels: the text of Xena and the fandom of Xena. The diegetic analysis of the series will allow us to establish the conception and origins of the series as something dense and complex that invites and suggests a plurality of interpretations. Spectators/fans invest time and effort in the show in a variety of ways to produce rich and varied interpretations and fandom content. Defining a serial phenomenon would therefore take us back to examining the correlation of: producer, text, fans, and context, which allows this expansion of the series in multiple directions. The analysis of Xena: Warrior Princess around a logic of densification will allow us to better understand certain phenomena of fandom around contemporary series.

Keyphrases: Fan, Fandom, Queer, Tv series, Seriality, Worlds, Phenomenon, Subtext, Xena: warrior princess, Feminism
La fiction en réalité virtuelle : une approche de recherche-création pour explorer le potentiel narratif et poétique d’une œuvre à 360°

The device known to the public as "virtual reality" offers a multisensory experience that encourages rethinking our habits of spectator perception. With the research component, I develop a reflection on the representation of reality in the cinema to better understand the relationship between the viewer and the image. Conducted with a view to jointly considering "narrative" and "device" our perspective is to look at the process of collaboration of the viewer, and to examine how with virtual reality, the "pact of representation" and the "spectatorial cognitivism" are upset. To do this, we will expand our study by relying on the technical aspects of virtual reality related to photorealism and sensorimotor immersion. The creation component, which takes the form of a short film in virtual reality, will explore the theme of the art of memory from the study of some real places that shelters it. The story takes place 10 years after an event of unknown origin decimated the world's population. Estéban, who survived the mysterious evil as a child, begins an exploration of architectural landscapes now in ruins, he will find a passion in photography. The narratological process of "mise en abyme" used in this short film will provide us with a first key to open avenues towards a reflection on fictionalization in its relationship with other artistic and representational phenomena, notably the contemporary practice called "urbex". .

Keyphrases: Virtual reality, Narratology, Urban exploration, Research and creation