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Author Information
Farhan Shafiq (LeapMind Inc)
Dr. Farhan has a PhD from Tokyo Institute of Technology and a Masters from Royal Institute of Technology Stockholm. He has a strong background in System on Chip (SoC) design and semiconductor technologies. Recently he has been working on edge computing related applications and developing CNN accelerators on FPGA devices at LeapMind Inc in Tokyo, Japan.
Antonio Tomas Nevado Vilchez (LeapMind Inc.)
Takato Yamada (LeapMind, inc.)
Sakyasingha Dasgupta (LeapMind, Inc.)
Robin Geyer (SAP)
Moin Nabi (SAP SE)
Crefeda Rodrigues (The University of Manchester)
Edoardo Manino (University of Southampton)
Edoardo Manino is a research fellow at the University of Southampton. Currently, he is finishing his PhD in machine learning and crowdsourcing under the supervision of Prof. Nicholas R. Jennings and Dr. Long Tran-Thanh. His research interests range from Bayesian learning to algorithmic game theory and, more recently, influence maximisation on social networks.
Alexantrou Serb (Univ. of Southampton)
Miguel A. Carreira-Perpinan (University of California, Merced)
Kar Wai Lim (National University of Singapore)
Bryan Kian Hsiang Low (National University of Singapore)
Rohit Pandey (Google Inc.)
Marie C White (Google)
Pavel Pidlypenskyi (Google)
Xue Wang (Google Inc.)
Christine Kaeser-Chen (Google Inc.)
Michael Zhu (Stanford University)
Suyog Gupta (Google)
Sam Leroux (Ghent University)
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2021 : Mixture-of-experts VAEs can disregard unimodal variation in surjective multimodal data »
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2022 : Collaborating with language models for embodied reasoning »
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2022 : Collaborating with language models for embodied reasoning »
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2023 Poster: Exploiting Correlated Auxiliary Feedback in Parameterized Bandits »
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2023 Poster: Equitable Model Valuation with Black-box Access »
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2023 Poster: Quantum Bayesian Optimization »
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2023 Poster: Batch Bayesian Optimization For Replicable Experimental Design »
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2023 Poster: Incentives in Private Collaborative Machine Learning »
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2022 Poster: Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization »
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2022 Poster: Learning to Navigate Wikipedia by Taking Random Walks »
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2022 Poster: Sample-Then-Optimize Batch Neural Thompson Sampling »
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2022 Poster: Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search »
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2021 Workshop: New Frontiers in Federated Learning: Privacy, Fairness, Robustness, Personalization and Data Ownership »
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2021 Poster: Differentially Private Federated Bayesian Optimization with Distributed Exploration »
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2021 Poster: Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning »
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2021 Poster: Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee »
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2021 Poster: Optimizing Conditional Value-At-Risk of Black-Box Functions »
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2021 Poster: Validation Free and Replication Robust Volume-based Data Valuation »
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2020 Poster: Variational Bayesian Unlearning »
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2020 Poster: Federated Bayesian Optimization via Thompson Sampling »
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2020 Poster: Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization »
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2019 : Break / Poster Session 1 »
Antonia Marcu · Yao-Yuan Yang · Pascale Gourdeau · Chen Zhu · Thodoris Lykouris · Jianfeng Chi · Mark Kozdoba · Arjun Nitin Bhagoji · Xiaoxia Wu · Jay Nandy · Michael T Smith · Bingyang Wen · Yuege Xie · Konstantinos Pitas · Suprosanna Shit · Maksym Andriushchenko · Dingli Yu · GaĆ«l Letarte · Misha Khodak · Hussein Mozannar · Chara Podimata · James Foulds · Yizhen Wang · Huishuai Zhang · Ondrej Kuzelka · Alexander Levine · Nan Lu · Zakaria Mhammedi · Paul Viallard · Diana Cai · Lovedeep Gondara · James Lucas · Yasaman Mahdaviyeh · Aristide Baratin · Rishi Bommasani · Alessandro Barp · Andrew Ilyas · Kaiwen Wu · Jens Behrmann · Omar Rivasplata · Amir Nazemi · Aditi Raghunathan · Will Stephenson · Sahil Singla · Akhil Gupta · YooJung Choi · Yannic Kilcher · Clare Lyle · Edoardo Manino · Andrew Bennett · Zhi Xu · Niladri Chatterji · Emre Barut · Flavien Prost · Rodrigo Toro Icarte · Arno Blaas · Chulhee Yun · Sahin Lale · YiDing Jiang · Tharun Kumar Reddy Medini · Ashkan Rezaei · Alexander Meinke · Stephen Mell · Gary Kazantsev · Shivam Garg · Aradhana Sinha · Vishnu Lokhande · Geovani Rizk · Han Zhao · Aditya Kumar Akash · Jikai Hou · Ali Ghodsi · Matthias Hein · Tyler Sypherd · Yichen Yang · Anastasia Pentina · Pierre Gillot · Antoine Ledent · Guy Gur-Ari · Noah MacAulay · Tianzong Zhang -
2019 Poster: Streaming Bayesian Inference for Crowdsourced Classification »
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2019 Poster: Implicit Posterior Variational Inference for Deep Gaussian Processes »
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2019 Spotlight: Implicit Posterior Variational Inference for Deep Gaussian Processes »
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2018 Poster: Alternating optimization of decision trees, with application to learning sparse oblique trees »
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2017 : Aligned AI Poster Session »
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2017 : Poster Session (encompasses coffee break) »
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2016 Poster: An ensemble diversity approach to supervised binary hashing »
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2015 Poster: A fast, universal algorithm to learn parametric nonlinear embeddings »
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2015 Poster: Inverse Reinforcement Learning with Locally Consistent Reward Functions »
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2011 Poster: A Denoising View of Matrix Completion »
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2007 Poster: People Tracking with the Laplacian Eigenmaps Latent Variable Model »
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