7,089 research outputs found

    Knowledge Distillation and Continual Learning for Optimized Deep Neural Networks

    Get PDF
    Over the past few years, deep learning (DL) has been achieving state-of-theart performance on various human tasks such as speech generation, language translation, image segmentation, and object detection. While traditional machine learning models require hand-crafted features, deep learning algorithms can automatically extract discriminative features and learn complex knowledge from large datasets. This powerful learning ability makes deep learning models attractive to both academia and big corporations. Despite their popularity, deep learning methods still have two main limitations: large memory consumption and catastrophic knowledge forgetting. First, DL algorithms use very deep neural networks (DNNs) with many billion parameters, which have a big model size and a slow inference speed. This restricts the application of DNNs in resource-constraint devices such as mobile phones and autonomous vehicles. Second, DNNs are known to suffer from catastrophic forgetting. When incrementally learning new tasks, the model performance on old tasks significantly drops. The ability to accommodate new knowledge while retaining previously learned knowledge is called continual learning. Since the realworld environments in which the model operates are always evolving, a robust neural network needs to have this continual learning ability for adapting to new changes

    International Academic Symposium of Social Science 2022

    Get PDF
    This conference proceedings gathers work and research presented at the International Academic Symposium of Social Science 2022 (IASSC2022) held on July 3, 2022, in Kota Bharu, Kelantan, Malaysia. The conference was jointly organized by the Faculty of Information Management of Universiti Teknologi MARA Kelantan Branch, Malaysia; University of Malaya, Malaysia; Universitas Pembangunan Nasional Veteran Jakarta, Indonesia; Universitas Ngudi Waluyo, Indonesia; Camarines Sur Polytechnic Colleges, Philippines; and UCSI University, Malaysia. Featuring experienced keynote speakers from Malaysia, Australia, and England, this proceeding provides an opportunity for researchers, postgraduate students, and industry practitioners to gain knowledge and understanding of advanced topics concerning digital transformations in the perspective of the social sciences and information systems, focusing on issues, challenges, impacts, and theoretical foundations. This conference proceedings will assist in shaping the future of the academy and industry by compiling state-of-the-art works and future trends in the digital transformation of the social sciences and the field of information systems. It is also considered an interactive platform that enables academicians, practitioners and students from various institutions and industries to collaborate

    DataComp: In search of the next generation of multimodal datasets

    Full text link
    Multimodal datasets are a critical component in recent breakthroughs such as Stable Diffusion and GPT-4, yet their design does not receive the same research attention as model architectures or training algorithms. To address this shortcoming in the ML ecosystem, we introduce DataComp, a testbed for dataset experiments centered around a new candidate pool of 12.8 billion image-text pairs from Common Crawl. Participants in our benchmark design new filtering techniques or curate new data sources and then evaluate their new dataset by running our standardized CLIP training code and testing the resulting model on 38 downstream test sets. Our benchmark consists of multiple compute scales spanning four orders of magnitude, which enables the study of scaling trends and makes the benchmark accessible to researchers with varying resources. Our baseline experiments show that the DataComp workflow leads to better training sets. In particular, our best baseline, DataComp-1B, enables training a CLIP ViT-L/14 from scratch to 79.2% zero-shot accuracy on ImageNet, outperforming OpenAI's CLIP ViT-L/14 by 3.7 percentage points while using the same training procedure and compute. We release DataComp and all accompanying code at www.datacomp.ai

    Harnessing the Power of the Arctic: Connecting tourists to nature through dog sledging activities.

    Get PDF
    This qualitative study explores the complex pockets of co-created interaction and throwntogetherness that produce meanings and value through an ethnographic sensory investigation of dog sledging tourism in Finnmark. I draw on a multirelational and multisensorial perspective on dog sledging, which means a holistic and socially constructed way of understanding Human-Animal Bonding (HAB) (DeMello, 2012). HAB enabled me to move beyond ethology when studying how culture, learning, emotions, communication, and cognition shaped interactions between tourist-mushers and dogs in arctic landscapes. The analysis unpacks the richness of the tourist-mushers interactions with sledge dogs by showing how physical senses and the arctic landscape bring about emotions and behavioural changes. The three main themes revolved around how the tourist-musher, through dog sledging, disconnected from everyday life and were reconnected with arctic landscapes. Theme one bonding, co-creation and interaction, consisting of the sub-themes bonding, co-creation and interactions, revealed pockets of meaning and value. Theme two, rhythm, through the sub- themes of time and flow, exposed the interconnectedness of reflection. Theme three, discovery mechanisms, with the sub-themes of physical senses, emotion, and learning, identified emotions of trust and empathy as learning tools that led to memory-making and mindfulness. I conclude that dog sledging tourism is a unique symbolic practice where nothing comes closer to experiencing nature's power. My study's symmetrical agency of humans and non-humans revealed new embodied ways of knowing. This knowledge strengthened and supported an embodied tourist experience approach (Everingham et al., 2021). Through my sensory ethnography of human and non-human encounters travelling together in nature, I address a research gap going beyond the advancement of Finnmarks’ regional tourism in Norway to a global understanding of what Arctic is. Keywords Dog sledging, Embodiment, Ethnography, Arctic landscape, Human-animal bonding, Relational materialis

    PROJECTIONS AMONGST GREAT POWERS: TRAJECTORIES WITHIN BOUNDED DETERRENCE AND OBSERVATIONS ON MISCALCULATION – U.S., CHINA, AND CUBAN CRISIS AS CASE STUDIES

    Get PDF
    This research seeks to examine the likely misperceptions, miscalculations, and misjudgments in the present environment surrounding Taiwan’s contested future which are likely to cross the nuclear threshold of either the United States or People’s Republic of China. This is illustrated primarily through the lens of the bounded deterrence model in order to investigate all possible nuclear deterrence outcomes of a given conflict, while offering an extension of theory based upon a four-part continua of bounded deterrence variables. This research investigates the present local deterrence environment and trends; deterrence dispositions of the United States, People’s Republic of China, the Republic of China, and numerous regional countries at present and foreseeable future; all possible nuclear deterrence outcomes between the United States and People’s Republic of China and implications; and the investigation of the seminal case study of the Cuban missile crisis as it pertains to today. Lastly, the research offers recommendations to ameliorate the possibilities of these misperceptions, miscalculations, and misjudgments from escalating to nuclear war. Namely, there are many “near misses” to nuclear war, notwithstanding the increasingly likely possibility of conventional conflict over Taiwan’s political future. The probability of conventional conflict over Taiwan turning into a nuclear war is greater than traditional American foreign policy wisdom recognizes. Therefore, the United States must be precisely clear in its intentions and to communicate in ways that not only the United States believes to be clear in maintaining deterrence, but that effectively transmits the necessary knowledge to the intended audience. Unless these trends of misjudgment and miscalculation are sorted and resolved, the concern McNamara had about the Cuban missile crisis is now thoroughly likely to be revisited in some future Taiwan crisis

    Saggitarius: A DSL for Specifying Grammatical Domains

    Full text link
    Common data types like dates, addresses, phone numbers and tables can have multiple textual representations, and many heavily-used languages, such as SQL, come in several dialects. These variations can cause data to be misinterpreted, leading to silent data corruption, failure of data processing systems, or even security vulnerabilities. Saggitarius is a new language and system designed to help programmers reason about the format of data, by describing grammatical domains -- that is, sets of context-free grammars that describe the many possible representations of a datatype. We describe the design of Saggitarius via example and provide a relational semantics. We show how Saggitarius may be used to analyze a data set: given example data, it uses an algorithm based on semi-ring parsing and MaxSAT to infer which grammar in a given domain best matches that data. We evaluate the effectiveness of the algorithm on a benchmark suite of 110 example problems, and we demonstrate that our system typically returns a satisfying grammar within a few seconds with only a small number of examples. We also delve deeper into a more extensive case study on using Saggitarius for CSV dialect detection. Despite being general-purpose, we find that Saggitarius offers comparable results to hand-tuned, specialized tools; in the case of CSV, it infers grammars for 84% of benchmarks within 60 seconds, and has comparable accuracy to custom-built dialect detection tools.Comment: OOPSLA 202

    A Very Socialist German Culture?: The GDR’s Use of German Classical Music Heritage for Domestic and International Legitimacy under Honecker (1971-1989)

    Get PDF
    In recent decades, with the growth of scholarly interest in GDR social and cultural history, the complexities and contradictions of GDR society have been unveiled. As a result, the conceptualisations of the GDR as, for instance, a ‘participatory dictatorship’ (Fulbrook) and ‘consensus dictatorship’(Jarausch) emerge to debunk the totalitarian characterisation of GDR society. This thesis complicates the GDR as a ‘participatory dictatorship’ by looking at the practices of German classical music heritage during the Honecker era. It asks how the Socialist Unity Party of Germany (SED) endeavoured to manipulate the heritage domestically and in the GDR’s trans-bloc cultural exchange with Britain for its political legitimacy and assesses the outcomes. In tracing the interactions between all involved social actors (i.e., state authorities, cultural institutions, the classical music intelligentsia, journalists and critics, and the public), this thesis demonstrates the complexities of all the actors’ relations to the heritage practices. As the thesis shows, significant to the complexities were factors such as the de facto existence of capitalism within GDR socialism, the SED’s reliance on the classical music intelligentsia’s contribution for its power consolidation, the non-state actors’ pursuits of their Eigensinn and hidden transcripts in navigating their relations with the SED government. In summation, this thesis proves that German classical music heritage’s policymaking and implementation in the GDR’s domestic scene and its trans-bloc cultural exchange cannot be understood as solely ‘top-down’ constructs. Instead, they were subject to changing dynamics and shaped by conflict and contradictions, cooperation and reconciliation between all the social actors involved
    • 

    corecore