{ "147495-21901110": { "datetime_modified":"20260407T121357", "datetime_start":"20260422T120000", "datetime_end":"20260422T140000", "has_end_time":1, "date_start":"2026-04-22", "date_end":"2026-04-22", "time_start":"12:00:00", "time_end":"14:00:00", "time_zone":"America\/Detroit", "event_title":"Xiaofeng Dai - Dissertation Defense", "occurrence_title":"", "combined_title":"Xiaofeng Dai - Dissertation Defense: What Does It Feel Like in the Nucleoid? The Biophysical Properties of the Bacterial Chromosome", "event_subtitle":"What Does It Feel Like in the Nucleoid? The Biophysical Properties of the Bacterial Chromosome", "event_type":"Presentation", "event_type_id":"16", "description":"Please join Xiaofeng Dai for their dissertation defense titled \"What Does It Feel Like in the Nucleoid? 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Advisors will discuss declaration requirements and what it means to be a Robotics Undergraduate student.\n", "occurrence_notes":null, "guid":"147362-21900899@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/147362", "building_id":"", "building_name":"", "campus_maps_id":"", "room":"", "location_name":"FRB 2000", "has_livestream":0, "cost":"", "tags":["Sessions"], "website":"https:\/\/sessions.studentlife.umich.edu\/p\/track\/16974", "sponsors":[ { "group_name":"Sessions @ Michigan", "group_id":"4791", "website":"https:\/\/sessions.studentlife.umich.edu\/" } ], "image_url":"", "styled_images":{ "event_thumb":"", "event_large":"", "event_large_2x":"", "event_large_lightbox":"", "group_thumb":"", "group_thumb_square":"", "group_large":"", "group_large_lightbox":"", "event_large_crop":"", "event_list":"", "event_list_2x":"", "event_grid":"", "event_grid_2x":"", "event_feature_large":"", "event_feature_thumb":"" }, "occurrence_count":1, "first_occurrence":21900899 } , "147779-21901962": { "datetime_modified":"20260415T154150", "datetime_start":"20260422T130000", "datetime_end":"20260422T143000", "has_end_time":1, "date_start":"2026-04-22", "date_end":"2026-04-22", "time_start":"13:00:00", "time_end":"14:30:00", "time_zone":"America\/Detroit", "event_title":"Marjorie Lee Browne Scholars Mini-Symposium", "occurrence_title":"", "combined_title":"Marjorie Lee Browne Scholars Mini-Symposium: Ian Augsburger, Ammar Eltigani, and Nicholas Simafranca", "event_subtitle":"Ian Augsburger, Ammar Eltigani, and Nicholas Simafranca", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"You are invited to attend a mini-symposium featuring the 14th cohort of MLB scholars completing the program this month. Each MLB scholar will give a 25-minute presentation of their research and have 5 minutes to answer questions from the audience. The MLB mini-symposium will take place on Wednesday, April 22 from 1:00-2:30pm in 1068EH. Food will be provided during the talks.\n\nPlease RSVP by Sunday, April 19 so that we know how many people to expect and can order food accordingly. https:\/\/forms.gle\/nY719sLt3CdtovG38\n---\nIan Augsburger: Efficient Learning of Dirichlet Simplex Models with Asymmetric Concentration Parameters\n\nAbstract: Learning latent topic or mixture models governed by Dirichlet distributions is a central problem in unsupervised learning, with applications ranging from topic modeling to population genetics and biological mixture analysis. Existing approaches\u2014most notably MCMC- and variational-based methods\u2014are often computationally expensive, sensitive to initialization, and particularly brittle in regimes where the Dirichlet concentration parameters are asymmetric or highly skewed.\n \nIn this work, we study the problem of efficiently learning Dirichlet Simplex Models, with special emphasis on the practically important but underexplored setting of asymmetric concentration parameters and regimes where individual components dominate the mixture. We show that the second-order moment structure of the observed data encodes the simplex geometry up to an orthogonal transformation on a low-dimensional subspace. Exploiting this structure, we reduce parameter recovery to the problem of learning an orthogonal map.\n \nBy introducing a geometry-aware metric aligned with the intrinsic covariance of the data, we obtain a simplified optimization scheme over the orthogonal group that is both stable and fast. Our approach leverages the polytope geometry of the simplex to enable parallelization over symmetry classes, significantly accelerating convergence. Empirically, the resulting algorithm performs remarkably well for asymmetric Dirichlet models, where standard MCMC-based methods often struggle. We view this framework as a step toward efficient, geometry-driven learning algorithms for broader classes of latent variable models.\n---\nAmmar Eltigani: Random Matrix Theory for High-Dimensional Machine Learning\n \nAbstract: The modern high-dimensional regime\u2014where the number of samples and their dimensions grow proportionally\u2014is ubiquitous in machine learning applications such as finance, healthcare, wireless communications, neuroscience, and computer vision. Despite the remarkable success of large-scale models in this setting, the underlying mathematical reasons remain only partially understood. Why, for instance, do overparameterized neural networks generalize well, and why do their risk curves exhibit double descent?\n \nThis expository talk begins by examining how low-dimensional intuitions fail in high dimensions, focusing on covariance estimation. We then introduce the Mar\u010denko\u2013Pastur law, which describes the limiting spectral distribution of sample covariance matrices for white noise. Finally, we discuss its generalization to arbitrary covariances and apply it to ridgeless linear regression, deriving a theoretical risk curve that displays the double-descent phenomenon.\n---\nNicholas Simafranca: Learning Low-Dimensional Representations with Heteroscedastic Data Sources\n\nAbstract: Principal component analysis (PCA) is a fundamental method for dimensionality reduction, but it treats all samples uniformly and can perform poorly when data come from sources with unequal noise levels. 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I will describe how this problem can be approached through alternating majorization-minimization and explain how a Riemannian block MM framework gives a route to proving convergence of a proximalized HePPCAT algorithm to a stationary point.", "occurrence_notes":null, "guid":"147779-21901962@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/147779", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1068", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics","Graduate Students"], "website":"https:\/\/forms.gle\/nY719sLt3CdtovG38", "sponsors":[ { "group_name":"Department of Mathematics", "group_id":"3791", "website":"" } ], "image_url":"", "styled_images":{ "event_thumb":"", "event_large":"", "event_large_2x":"", "event_large_lightbox":"", "group_thumb":"", "group_thumb_square":"", "group_large":"", "group_large_lightbox":"", "event_large_crop":"", "event_list":"", "event_list_2x":"", "event_grid":"", 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These processes drive many adaptive behaviors, but we know little about how cognitive traits evolve in wild populations. I will use Polistes wasps as a model to investigate the links between cognition, behavior, and fitness over multiple generations in the field. 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In the basic model, skills expand the set of feasible payoffs, while altruism guides the decision maker\u2019s choice. Greater skills need not increase social welfare, because such expansions combine a positive frontier effect with an ambiguous substitution effect, potentially toward actions that are privately attractive but socially harmful. This ambiguous effect of skills on development is referred to as the \u201clottery of the technology\u201d and disappears when altruism is high enough to ensure that new opportunities created by skills are used only when they raise social welfare. Extensions of the model show that 1) endogenous technological change makes altruism even more influential in the long run 2) the effect of stronger institutions is subject to a \u201clottery of alignment of interests\u201d between policymakers\u2019 private gains and social welfare, unless policymakers\u2019 altruism is high enough to ensure the good use of institutional power, making institutions a lever of altruism rather than a substitute and 3) allowing altruism to be group-specific shows that only universal altruism guarantees the effective use of skill improvements. This framework speaks to many contemporary and historical events and leads to the conclusion that ensuring long-term development requires both the selection of altruistic leaders and a population shift in the distribution of altruism.", "occurrence_notes":null, "guid":"144125-21894695@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/144125", "building_id":"1005177", "building_name":"North Quad", "campus_maps_id":"553", "room":"4300", "location_name":"North Quad", "has_livestream":0, "cost":"", "tags":["Economics","seminar","Development"], "website":"http:\/\/www.lsa.umich.edu\/econ", "sponsors":[ { "group_name":"Department of Economics", "group_id":"3302", "website":"http:\/\/www.lsa.umich.edu\/econ" }, { "group_name":"Economic Development Seminar", "group_id":"3557", "website":"" }, { "group_name":"Department of Economics Seminars", "group_id":"3566", "website":"" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/01\/event_144125_original-1.png", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/event_large_2x\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/01\/event_144125_original-1.png", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/group_thumb\/media\/attachments\/2026\/01\/event_144125_original-1.png", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/group_thumb_square\/media\/attachments\/2026\/01\/event_144125_original-1.png", "group_large":"https:\/\/events.umich.edu\/media\/cache\/group_large\/media\/attachments\/2026\/01\/event_144125_original-1.png", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/group_large_lightbox\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/event_large_crop\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_list":"https:\/\/events.umich.edu\/media\/cache\/event_list\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/event_grid_2x\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/event_feature_large\/media\/attachments\/2026\/01\/event_144125_original-1.png", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_feature_thumb\/media\/attachments\/2026\/01\/event_144125_original-1.png" }, "occurrence_count":1, "first_occurrence":21894695 } }