1,875 research outputs found

    Protest and reform :

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    Continual Learning in the Teacher-Student Setup: Impact of Task Similarity

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    Continual learning—the ability to learn many tasks in sequence—is critical for artificial learning systems. Yet standard training methods for deep networks often suffer from catastrophic forgetting, where learning new tasks erases knowledge of the earlier tasks. While catastrophic forgetting labels the problem, the theoretical reasons for interference between tasks remain unclear. Here, we attempt to narrow this gap between theory and practice by studying continual learning in the teacher-student setup. We extend previous analytical work on two-layer networks in the teacher-student setup to multiple teachers. Using each teacher to represent a different task, we investigate how the relationship between teachers affects the amount of forgetting and transfer exhibited by the student when the task switches. In line with recent work, we find that when tasks depend on similar features, intermediate task similarity leads to greatest forgetting. However, feature similarity is only one way in which tasks may be related. The teacher-student approach allows us to disentangle task similarity at the level of \textbackslashemphreadouts (hidden-to-output weights) as well as \textbackslashemphfeatures (input-to-hidden weights). We find a complex interplay between both types of similarity, initial transfer/forgetting rates, maximum transfer/forgetting, and the long-time (post-switch) amount of transfer/forgetting. Together, these results help illuminate the diverse factors contributing to catastrophic forgetting

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    Mentalizing under Uncertainty: Dissociated Neural Responses to Ambiguous and Unambiguous Mental State Inferences

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    The ability to read the minds of others (i.e., to mentalize) requires that perceivers understand a wide range of different kinds of mental states, including not only others’ beliefs and knowledge but also their feelings, desires, and preferences. Moreover, although such inferences may occasionally rely on observable features of a situation, perceivers more typically mentalize under conditions of “uncertainty,” in which they must generate plausible hypotheses about a target's mental state from ambiguous or otherwise underspecified information. Here, we use functional neuroimaging to dissociate the neural bases of these 2 distinct social–cognitive challenges: 1) mentalizing about different types of mental states (beliefs vs. preferences) and 2) mentalizing under conditions of varying ambiguity. Although these 2 aspects of mentalizing have typically been confounded in earlier research, we observed a double dissociation between the brain regions sensitive to type of mental state and ambiguity. Whereas ventral and dorsal aspects of medial prefrontal cortex responded more during ambiguous than unambiguous inferences regardless of the type of mental state, the right temporoparietal junction was sensitive to the distinction between beliefs and preferences irrespective of certainty. These results underscore the emerging consensus that, rather than comprising a single mental operation, social cognition makes flexible use of different processes as a function of the particular demands of the social context

    The WASp-like protein Scar regulates macropinocytosis, phagocytosis and endosomal membrane flow in Dictyostelium

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    Scar, a member of the WASp protein family, was discovered in Dictyostelium discoideum during a genetic screen for second-site mutations that suppressed a developmental defect. Disruption of the scar gene reduced the levels of cellular F-actin by 50%. To investigate the role of Scar in endocytosis, phagocytosis and endocytic membrane trafficking, processes that depend on actin polymerization, we have analyzed a Dictyostelium cell line that is genetically null for Scar. Rates of fluid phase macropinocytosis and phagocytosis are significantly reduced in the scar- cell-line. In addition, exocytosis of fluid phase is delayed in these cells and movement of fluid phase from lysosomes to post-lysosomes is also delayed. Inhibition of actin polymerization with cytochalasin A resulted in similar phenotypes, suggesting that Scar-mediated polymerization of the actin cytoskeleton was important in the regulation of these processes. Supporting this conclusion, fluorescence microscopy revealed that some endo-lysosomes were ringed with F-actin in control cells but no F-actin was detected associated with endo-lysosomes in Scar null cells. Disruption of the two genes encoding the actin monomer sequestering protein profilin in wild-type cells causes defects in the rate of pinocytosis and fluid phase efflux. Consistent with a predicted physical interaction between Scar and profilin, disrupting the scar gene in the profilin null background results in greater decreases in the rate of fluid phase internalization and fluid phase release compared to either mutant alone. Taken together, these data support a model in which Scar and profilin functionally interact to regulate internalization of fluid and particles and later steps in the endosomal pathway, probably through regulation of actin cytoskeleton polymerization

    Structural Connectivity of the Developing Human Amygdala

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    <div><p>A large corpus of research suggests that there are changes in the manner and degree to which the amygdala supports cognitive and emotional function across development. One possible basis for these developmental differences could be the maturation of amygdalar connections with the rest of the brain. Recent functional connectivity studies support this conclusion, but the structural connectivity of the developing amygdala and its different nuclei remains largely unstudied. We examined age related changes in the DWI connectivity fingerprints of the amygdala to the rest of the brain in 166 individuals of ages 5-30. We also developed a model to predict age based on individual-subject amygdala connectivity, and identified the connections that were most predictive of age. Finally, we segmented the amygdala into its four main nucleus groups, and examined the developmental changes in connectivity for each nucleus. We observed that with age, amygdalar connectivity becomes increasingly sparse and localized. Age related changes were largely localized to the subregions of the amygdala that are implicated in social inference and contextual memory (the basal and lateral nuclei). The central nucleus’ connectivity also showed differences with age but these differences affected fewer target regions than the basal and lateral nuclei. The medial nucleus did not exhibit any age related changes. These findings demonstrate increasing specificity in the connectivity patterns of amygdalar nuclei across age.</p></div

    Developing a truck rollover risk calculator for south africa

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    The Static Rollover Threshold (SRT) is an important metric for characterising a heavy vehicle’s inherent stability and risk of rollover. Current methods of assessing SRT include a tilt-table test and multi-body dynamics simulation which can be costly, time-consuming and often require significant technical expertise or technical vehicle data not normally accessible to the public. Simplified calculation methods exist, but a remaining challenge exists to reduce the required level of user expertise and input data to make the assessment useable by, for example, fleet insurers who would have an interest in SRT information. In this paper we investigate the use of simplified calculations prescribed by the New Zealand Land Transport Rule (NZLTR) and UNECE 111 as the basis for the development of a user-friendly SRT calculator. The calculation results were validated against a multi-body dynamics model using TruckSIM for the case of a rigid truck for a range of vehicle suspension and mass properties. The NZLTR and ‘interpolated’ UNECE 111 methods resulted in the smallest errors compared with TruckSIM, averaging 6-7% in absolute error over the 16 scenarios assessed. Maximum errors occurred when the ratio between drive axle and steer axle roll stiffness was at its highest (at a ratio of 4.7:1). The UNECE 111 method was then used as the basis for a Python-based SRT calculator tool. The tool demonstrates how pre-loaded technical vehicle data and logic can be used to minimise the required user expertise and hence make SRT calculation feasible by nontechnical users in the fleet insurance industry in South Africa.Papers presented at the 40th International Southern African Transport Conference on 04 -08 July 202
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