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Adji B. Dieng, International Conference on learning Representation (ICLR), 2017, A. The RNN component of the model captures syntax while the topic model component captures semantic. Title. It consists in positing a family of distributions and finding the distribution in this family that better approximates the true posterior. arxiv Poster Home; Random; Nearby; Log in; Settings; Donate; About Wikipedia; Disclaimers; Subcategories. This AI Expert From Senegal Is Helping Showcase Africans In STEM. / [2] She won one of the prizes for the Senegalese Olympiad ("Concours Général") in Philosophy, was selected to participate in the 2005 Excellence camp organized by the Pathfinder Foundation for Education and Development, a non-profit founded by Cheick Modibo Diarra, and was subsequently selected to participate in a competitive exam organized for African girls in partnership between the Central Bank for West African States and the Pathfinder Foundation. Articles Cited by Co-authors. She is currently an Artificial Intelligence Research Scientist at Google Brain in Mountain View, California. Adji Bousso Dieng is a PhD Candidate at Columbia University where she is jointly advised by David Blei and John Paisley. Adji B. Dieng, Probability - Fall 2014, Science meets Engineering of Deep Learning (SEDL), Columbia's GSAS Student Successes Website, 2nd Symposium on Advances in Approximate Bayesian Inference, deep generative models and structured data, Women in Machine Learning Mentorship Roundtable, Carnegie Mellon University Machine Learning Seminar, IPAM Workshop on Interpretable Learning in Physical Systems, University of Maryland's Rising Stars in Machine Learning seminar, New York Machine Learning and Artificial Intelligence Meetup, South England Natural Language Processing Meetup, Dec 2019: Happy to be serving as advisor for the, Sep 2019: I was very glad to serve as Area Chair for the, Aug 2019: I will be giving a two-hour lecture on deep generative models at this year's, May 2019: I co-organized an ICLR workshop on, Sep 2018: I will be spending this Fall semester at, May 2018: I am excited to be interning with Yann LeCun at. Adji B. Dieng, The decoder of a Skip-VAE is a neural network whose hidden states--at every layer--condition on the latent variables. Adji Bousso Dieng 2 Publications & Preprints A. Jianfeng Gao, The DETM learns smooth topic trajectories by defining a random walk prior over the embeddings of the topics. / However minimizing the KL leads to approximations that underestimate posterior uncertainty. B. Dieng, R. Ranganath, J. Altosaar, and D. M. Blei. Avoiding Latent Variable Collapse with Generative Skip Models This results in a stronger dependence between observations and their latents and therefore avoids latent variable collapse. https://cpsc.yale.edu/event/cs-colloquium-adji-bousso-dieng Noisin: Unbiased Regularization for Recurrent Neural Networks In 2013, Dieng accepted a position as a Junior Professional Associate at the World Bank working on risk modeling in the Department of Market and Counterparty Risk. /. Alp Kucukelbir, Slides Augment and Reduce: Stochastic Inference for Large Categorical Distributions. arxiv AI expert Adji Bousso Dieng to become first Black female faculty member at SEAS. B. Dieng, Y. Kim, A. M. Rush, and D. M. Blei. Adji Bousso Dieng CV / Google Scholar / LinkedIn / Github / Twitter / Email: abd2141 at columbia dot edu I am a Ph.D candidate in the department of Statistics at Columbia University where I am jointly being advised by David Blei and John Paisley . [9] Dieng noticed the inaccurate portrayal of Africa in the media, which was further accentuated during the COVID-19 global crisis. New website by Senegalese AI expert spotlights Africans in STEM. / The Dynamic Embedded Topic Model Topic Modeling in Embedding Spaces Noisin: Unbiased Regularization for Recurrent Neural Networks. Jaan Altosaar, This divergence leads to an upper bound of the model evidence (called CUBO) and overdispersed posterior approximations. Adji Bousso Dieng is a Senegalese Computer Scientist and Statistician working in the field of Artificial Intelligence.Her research bridges probabilistic graphical models and deep learning to discover meaningful structure from unlabelled data. John Paisley John Paisley, Reweighted Expectation Maximization Achieving these two goals will benefit many applications. www.mobilewiki.org adji bousso dieng Adji Bousso Dieng. Our paper proposes the Chi-divergence for variational inference. In this episode, i'm joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University. Cited by. However softmax does not scale well when there are many categories. Code Her research is in Artificial Intelligence and Statistics, bridging probabilistic graphical models and deep learning. LinkedIn  /  Slides. This solution leads to the Skip-VAE--a deep generative model that avoids latent variable collapse. Form a generative model of documents that defines the likelihood of a word as a Categorical whose natural parameter is the dot product between the word embedding and its assigned topic's embedding. Adji Bousso Dieng. The word embeddings allow the DETM to generalize to rare words. [10][11] Another goal of the initiative is to provide role models to young Africans, who often grow up without seeing role models that look like them due to a lack of visibility. Verified email at columbia.edu - Homepage. The criterion for learning is a divergence measure. In my research, I work on combining probabilistic graphical modeling and deep learning to design models for structured high-dimensional data such as text. Dawen Liang, / Adji B. Dieng, The DETM is fit using structured amortized variational inference with LSTMs. This category has the following 7 subcategories, out of 7 total. Adji Bousso Dieng is currently a Research Scientist at Google AI, and will be starting as an assistant professor at Princeton University in 2021. B. Dieng, C. Wang, J. Gao, and J. W. Paisley. Posterior inference is done after the model is fitted. [3] The majority of people do not know about the rich history of STEM and AI developments made possible by Africans. Her research focuses on combining probabilistic graphical modeling and deep learning to design models for structured high-dimensional data. Adji B. Dieng*, Dustin Tran, Statistical Methods for Finance - Spring 2016 Francisco R. J. Ruiz*, Love Love: AI and ML in Tennis with Stephanie Kovalchik [4], Dieng has authored/co-authored several papers published in AI venues such as NeurIPS, ICML, ICLR, AISTATS, and TACL. Not only has Adji Bousso Dieng, an AI researcher from Senegal, contributed to the field of generative modeling and about to become one of the first black female faculty in Computer Science in the Ivy League, she is also helping Africans in STEM tell their own success stories. View Adji Bousso Dieng’s profile on LinkedIn, the world’s largest professional community. [2] Dieng was one of 15 siblings, and to support the family, her parents owned a business selling fabric. Variational inference is an efficient approach for estimating posterior distributions. Augment and Reduce: Stochastic Inference for Large Categorical Distributions Recent Changes. Adji Bousso Dieng is a PhD Candidate at Columbia University where she is jointly advised by David Blei and John Paisley. Artificial Intelligence (AI) researcher Adji Bousso Dieng will become the first black woman faculty to join Princeton’s School of Engineering in its 100-year history. Dieng is currently an AI researcher at Google, working in the field of generative modeling. I also work on variational methods as an inference framework for fitting these models. Adji Bousso Dieng is a Senegalese Computer Scientist and Statistician working in the field of Artificial Intelligence. [3] Her father passed away when she was four years old, yet her mother still ensured that education was a priority in the family. Dieng spent her third year of Telecom ParisTech's curriculum at Cornell University. [3], Dieng is currently working at Google Brain as a Research Scientist in Artificial Intelligence (AI). Transactions of the Association for Computational Linguistics (TACL), 2020, A. [1] Dieng recently founded the non-profit “The Africa I Know” (TAIK) with the goal to inspire young Africans to pursue careers in STEM and AI by showcasing African role models, informing the general public about developments in STEM and AI by Africans, and educating the general public about the rich history of Africa. Adji Bousso Dieng's articles on arXiv [1] arXiv:1907.05545 [pdf, other] Title: The Dynamic Embedded Topic Model ... Adji B. Dieng, and David M. Blei. Francisco J. R. Ruiz, A tensorflow-based library for probabilistic programming. However they tend to have very high capacity and overfit very easily. B. Dieng, D. Tran, R. Ranganath, J. W. Paisley and D. M. Blei. A&R is built on two ideas: latent variable augmentation and stochastic variational expectation maximization. Prior to joining Columbia I worked as a Junior Professional Associate at the World Bank. Francisco R. J. Ruiz, Github  /  David M. Blei Slides. Adji dan agung - View adji bousso linkedin, on linkedin, the largestprofessional. Chong Wang, It consists in positing a family of distributions and finding the distribution in this family that better approximates the true posterior. arxiv Dieng was born and raised in Kaolack, Senegal. [9] TAIK inspires young Africans to follow careers in STEM and AI, informs people about the contributions in STEM and AI by Africans, and educates about the rich history of Africa. Code / Maja Rudolph, Machine Learning Statistics Deep Learning. John Paisley, [2] She received a scholarship to study abroad after winning this competition. May 2018: I co-authored two papers that are appearing at this year's ICML: "Augment and Reduce: Stochastic Inference for Large Categorical Distributions" and "Noisin: Unbiased Regularization for Recurrent Neural Networks". Adji B. Dieng, Her research is in Artificial Intelligence and Statistics, bridging probabilistic graphical models and deep learning. To fit the model we leverage moment matching to learn rich proposals to estimate the EM objective. Adji Bousso Dieng, Dustin Tran, Rajesh Ranganath, John Paisley, David Blei Abstract Variational inference (VI) is widely used as an efficient alternative to Markov chain Monte Carlo. September 16, 2020 September 15, 2020 The African Mirror Adji Bousso Dieng, artificial intelligence, Senegalese AI expert. Adji gave a talk on April, 28th about her work on TopicRNN and variational inference. [4] She then attended Télécom ParisTech, a top French public institution of higher education and research of engineering located in Palaiseau, France. [2], While abroad, Dieng attended Lycée Henri IV, a public secondary school located in Paris. My goal as a Machine Learning researcher is twofold. /. You searched for: Author Dieng, Adji Bousso Remove constraint Author: Dieng, Adji Bousso Author Wang, Fei Remove constraint Author: Wang, Fei Language English Author Dieng, Adji Bousso Remove constraint Author: Dieng, Adji Bousso Author Wang, Fei Remove constraint Author: Wang, Fei Language English Speaking by phone from her home in New York, Dieng said her mother had taught her to value education. Variational inference is an efficient approach for estimating posterior distributions. Code International Conference on Machine Learning (ICML) (Submitted) [5] Dieng worked with David Blei and John Paisley to bridge Probabilistic Graphical Modeling and Deep Learning with the goal of discovering meaningful patterns from unlabelled data for applications in natural language processing, computer vision, and healthcare. Neural Information Processing Systems (NIPS), 2017. Francisco R. J. Ruiz, International Conference on Machine Learning (ICML), 2018, A. Sort. We propose a new regularization method called Noisin. Under submission at Journal of Machine Learning Research (JMLR) Adji Bousso Dieng is a Senegalese Computer Scientist and Statistician working in the field of Artificial Intelligence. / Twitter  /  Adji Bousso has 9 jobs listed on their profile. CUBO can be used alongside the usual ELBO to sandwich-estimate the model evidence. David M. Blei My work is funded by a Columbia Dean Fellowship and a Google PhD Fellowship in Machine Learning. In this episode, i’m joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University. David M. Blei The topic model and the RNN parameters are learned jointly using amortized variational inference. In this episode, Sam Charrington is joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University to discuss two of her recent papers, “Noisin: Unbiased Regularization for Recurrent Neural Networks” and TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency. Come next September, Adji Bousso Dieng — an expert in artificial intelligence and machine learning — will join the faculty of the School of Engineering and Applied Science (SEAS) as a tenure-track assistant professor, becoming the first Black female faculty member in the history of SEAS and the first Black faculty member ever in the Department of Computer Science (COS). wikipedia. img. Dieng is supported by a Dean Fellowship from Columbia University. Advanced Data Analysis - Fall 2017 Her work at Columbia is about combining probabilistic graphical modeling and deep learning to design better generative models. Prescribed Generative Adversarial Networks. Her research is in Artificial Intelligence and Statistics, bridging probabilistic graphical models and deep learning. arxiv /. Adji Bousso Dieng; D. Jeff Dean (computer scientist) G. Ramanathan V. Guha; H. Urs Hölzle; S. Amit Singhal; Ramakrishnan Srikant; T. Sebastian Thrun This page was last edited on 25 August 2020, at 22:08 (UTC). International Conference on Machine Learning (ICML), 2018 Slides Adji Bousso Dieng is a PhD student at Columbia University, supervised by Prof. David Blei and John Paisley. The resulting Embedded Topic Model (ETM) learns interpretable topics and word embeddings and is robust to large vocabularies that include rare words and stop words. Adji Bousso Dieng will be Princeton's School of Engineering's first Black female faculty. arxiv read more. Rajesh Ranganath, David M. Blei TopicRNN: A Recurrent Neural Network with Long Range Semantic Dependency. Under Review at Journal of Machine Learning Research (JMLR). Poster Thomas Kipf. David M. Blei, [4], After working at the World Bank for one year, Dieng started her PhD in Statistics at Columbia University. VI introduces an undesirable amortization gap and often causes latent variable collapse. Code. Our paper proposes the Chi-divergence for variational inference. View adji bousso profile dieng's linkedin, world's the largestcommunity. [2] She was also awarded a Master in Applied Statistics from Cornell University in Ithaca, New York. Speaker Bio: Adji Bousso Dieng is a PhD candidate at Columbia University where she works with David Blei and John Paisley. Code TopicRNN is a deep generative model of language that marries RNNs and topic models to capture long-term dependencies. Under Review at Journal of Machine Learning Research (JMLR). One challenge in modeling sequential data with RNNs is the inability to capture long-term dependencies. Linear Regression Models - Spring 2015 arxiv. The typical workaround is variational inference (VI) which maximizes a lower bound to the log marginal likelihood of the data. Topic Modeling in Embedding Spaces. Neural Information Processing Systems (NeurIPS), 2017 Probability and Statistics for Data Science - Fall 2015 Google Scholar  /  The most used divergence is the Kullback-Leibler (KL) divergence. Define words and topics in the same embedding space. Our paper proposes a simple solution that relies on skip connections. Recurrent neural networks are very effective at modeling sequential data. However they suffer from a problem known as "latent variable collapse". [5], In 2021, Dieng will join the Department of Computer Science at Princeton University as a tenure-track Assistant Professor. We propose to use expectation maximization (EM) instead. / Sort by citations Sort by year Sort by title. [8], Dieng is the founder of the non-profit called “ The Africa I Know”, with the mission to positively change the narrative about Africa and provide opportunities to young Africans. Prescribed Generative Adversarial Networks Under review at Transactions of the Association for Computational Linguistics (TACL), 2019 Noisin significantly outperforms Dropout on both the Penn TreeBank and the Wikitext-2 datasets on a language modeling task. Text is available under the Creative Commons Attribution-ShareAlike License; additional terms … Adji Bousso Dieng SCIENCE, TECH AND INNOVATION . Dieng is supported by a Dean Fellowship from Columbia University. Edward: A Library for Probabilistic Modeling, Inference, and Criticism [12], www.wikipedian.net Adji Bousso Dieng Adji Bousso Dieng, Zavod za farmacijo in preizkušanje zdravil, Public Agency of the Republic of Slovenia for Medicinal Products and Medical Devices, Public Agency of the Republic of Slovenia for Medicines and Medical Devices, Agency of the Republic of Slovenia for Medicines and Medical Devices, UMMC Museum of Military and Automotive Equipment, 2020-21 Holy Cross Crusaders men's ice hockey season, 2020-21 Bentley Falcons men's ice hockey season, Javna agencija RS za zdravila in medicinske pripomočke, Deep Probabilistic Graphical Modeling, Founder of The Africa I Know, Google PhD Fellowship in Machine Learning, Rising Star in Machine Learning, Columbia University Dean Fellowship, Cornell Institute for African Development Fellowship, Artificial Intelligence, Computer Science, Statistics, 2020 - Named one of the 100 Most Influential Africans, 2019 - Rising Star in Machine Learning (University of Maryland), 2019 - Google PhD Fellowship in Machine Learning, 2014 - Columbia University Dean Fellowship, 2013 - Cornell Institute for African Development Fellowship, 2006 - Senegalese Government Excellence Scholarship, 2006 - Laureate du Concours General (Senegalese Olympiad, Philosophy), A. Noisin relies on the notion of "unbiased" noise injection. arxiv A. The slides are available here. I am a Ph.D candidate in the department of Statistics September 16, 2020 September 15, 2020 The African Mirror Adji Bousso Dieng, artificial intelligence, Senegalese AI expert. I hold a Diplome d'Ingenieur from Telecom ParisTech and spent the third year of Telecom ParisTech's curriculum at Cornell University where I earned a Master in Statistics. We propose a method called A&R that scales learning with categorical distributions. Adji B. Dieng, David M. Blei In 2021, she will start her tenure-track faculty position at Princeton University becoming the first Black female faculty member in the School of Engineering and Applied Science as well as the first Black faculty member ever in the Department of Computer Science. B. Dieng and J. Paisley. [3][4] Dieng's doctoral work has received various forms of recognition including the Google PhD Fellowship in Machine Learning[3] and a Rising Star in Machine Learning nomination by the University of Maryland. Reweighted Expectation Maximization. Variational Inference via χ Upper Bound Minimization. International Conference on Learning Representations (ICLR), 2017 In natural language these long-term dependencies come in the form of semantic dependencies. arxiv … Read the rest. Artificial Intelligence and Statistics (AISTATS), 2019, A. GROWING up in a trading town in Senegal, Adji Bousso Dieng loved school and had a particular talent for maths. Adji B. Dieng, The DETM models each word with a categorical distribution whose parameter is given by the inner product between the word embedding and an embedding representation of its assigned topic at a particular time step. An extension of the Embedded Topic Model to corpora with temporal dependencies. The family business was selling fabric, and neither of her parents finished school. Key ingredients: noise, entropy regularization, and Hamiltonian Monte Carlo. Adji Bousso Dieng wants to give young Africans the inspiring examples she missed out on. — Adji Bousso Dieng (@adjiboussodieng) August 30, 2020. My first goal is to combine deep learning and probabilistic graphical modeling to design models that are expressive and powerful enough to capture meaningful representations of high-dimensional structured data. In 2013 she graduated from Télécom ParisTech, earning her Diplome d'ingenieur (a degree in Engineering from France's Grandes Ecoles system). / Bio: Adji Bousso Dieng is a PhD Candidate at Columbia University where she is jointly advised by David Blei and John Paisley. Dieng was also the second black woman to graduate from the department of Statistics at Columbia University. This divergence leads to an upper bound of the model evidence (called CUBO) and overdispersed posterior approximations. Turns out EM learns better deep generative models than VI as measured by predictive log-likelihood. /. Adji Bousso Dieng, D. Tran, R. Ranganath, J. Paisley, D. Blei 2017 Variational inference (VI) is widely used as an efficient alternative to Markov chain Monte Carlo. Rajesh Ranganath, The criterion for learning is a divergence measure. One of the current staples of unsupervised representation learning is variational autoencoders (VAEs). /. The most used divergence is the Kullback-Leibler (KL) divergence. Yoon Kim, Columbia University. / Adji Bousso Dieng will be Princeton’s School of Engineering’s first Black female faculty. Year; Edward: A library for probabilistic modeling, inference, and criticism. One wide parameterization of a categorical distribution is the softmax. [5] She left the World Bank the following summer, in 2014, after being awarded a Columbia University Dean Fellowship to start a PhD in Statistics. Avoiding Latent Variable Collapse With Generative Skip Models. Adji B. Dieng, David M. Blei CUBO can be used alongside the usual ELBO to sandwich-estimate the model evidence. at Columbia University where I am jointly being advised by David Blei Statistical Machine Learning - Spring 2019 Research scientist Adji Bousso Dieng, from Senegal, launched the website "The Africa I Know" to highlight experts in STEM in Africa. International Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Variational Inference via Chi Upper Bound Minimization B. Dieng, F. J. R. Ruiz, and D. M. Blei. Adji B. Dieng, I am fortunate to have been a teaching assistant for the following courses at Columbia University. Categorical distributions are ubiquitous in Statistics and Machine Learning. However minimizing the KL leads to approximations that underestimate posterior uncertainty. I did my undergraduate training in France where I attended Lycee Henri IV and Telecom ParisTech--France's Grandes Ecoles system. (2) How can we evaluate predictive log-likelihood for GANs to assess how they generalize to new data? [2], During high school, Dieng was recognized for her academic achievements. arxiv / CV  /  Dieng is supported by a Dean Fellowship from Columbia University. [2] Her father never attended school, and her mother started but did not complete high school. and John Paisley. But with a dearth of career role models, she had no idea which path to follow. [6] Prior to her work at Google, Dieng interned at many major companies in AI such as Microsoft Research in Seattle, DeepMind in London, and she also worked with Yann LeCun at Facebook AI Research. International Conference on Machine Learning (ICML), 2018 Her research bridges probabilistic graphical models and deep learning to discover meaningful structure from unlabelled data. My second goal is to develop efficient, scalable, and generic algorithms for learning with these models. Dieng attended Kaolack's public schools for both elementary and high school. Email: abd2141 at columbia dot edu. B. Dieng, F. J. R. Ruiz, D. M. Blei, and M. Titsias. Journal of Machine Learning Research (JMLR) (Submitted) TopicRNN: A Recurrent Neural Network With Long-Range Semantic Dependency This paper describes a solution to two important problems in the GAN literature: (1) How can we maximize the entropy of the generator of a GAN to prevent mode collapse? International Conference on Machine … This two-step procedure shies away from the current VAE approach of bundling together model fitting and posterior inference. Dustin Tran, Michalis Titsias David M. Blei Her research bridges probabilistic graphical ... More info. arxiv Michalis Titsias, Noisin is an explicit regularizer--it's objective function can be decomposed as the original objective for the deterministic RNN and a non-negative data-dependent term. Adji Bousso Dieng. Alexander M. Rush, [7] She will be the first Black faculty in Computer Science in Princeton's history, the first Black woman tenure-track faculty in Princeton's School of Engineering, and the second Black woman tenure-track faculty in Computer Science across the Ivy League. In an interview with Forbes, she … Dec 2017: I am glad to be part of the mentors for this year's, Yahoo Research Seminar Series, New York, NY, July 2019, Microsoft Research Cambridge, Cambridge, UK, January 2019, Harvard University NLP Group Meeting, Cambridge, MA, April 2018, MSR AI, Microsoft Research, Redmond, WA, August 2017, SSLI Lab, University of Washington, Seattle, WA, August 2017, IBM TJ Watson Research, Yorktown Heights, NY, December 2016, Microsoft Research, Redmond, WA, August 2016. / Importantly, we separate posterior inference and model fitting. Maximum likelihood in deep generative models is hard. Cited by. , F. J. R. Ruiz, D. M. Blei international Conference on Machine learning researcher is.. Of semantic dependencies: a library for probabilistic modeling, inference, and M. Titsias new!, the world Bank for one year, Dieng is a neural Network whose hidden states -- at every --! From Cornell University in Ithaca, new York, Dieng will be Princeton 's of! 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( 2 ) How can we evaluate predictive log-likelihood for GANs to assess they... Often causes latent variable collapse '' noise injection ; additional terms … wikipedia the EM objective Dieng said mother. ; Settings ; Donate ; about wikipedia ; Disclaimers ; Subcategories home ; Random ; ;.

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