- Grace Deng, David S. Matteson:
Bayesian spillover graphs for dynamic networks. UAI 2022: 529-538 - Christophe Denis, Charlotte Dion-Blanc, Laure Sansonnet:
Multiclass classification for Hawkes processes. UAI 2022: 539-547 - Anthony DiGiovanni, Ambuj Tewari:
Balancing adaptability and non-exploitability in repeated games. UAI 2022: 559-568 - Or Dinari, Oren Freifeld:
Variational- and metric-based deep latent space for out-of-distribution detection. UAI 2022: 569-578 - Or Dinari, Oren Freifeld:
Revisiting DP-Means: fast scalable algorithms via parallelism and delayed cluster creation. UAI 2022: 579-588 - Fan Ding, Yexiang Xue:
X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning. UAI 2022: 589-598 - Punit Pankaj Dubey, Bhisham Dev Verma, Rameshwar Pratap, Keegan Kang
:
Improving sign-random-projection via count sketch. UAI 2022: 599-609 - Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis:
ResIST: Layer-wise decomposition of ResNets for distributed training. UAI 2022: 610-620 - Varun Embar, Sriram Srinivasan, Lise Getoor:
Learning explainable templated graphical models. UAI 2022: 621-630 - Hannes Eriksson
, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis:
SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning. UAI 2022: 631-640 - Akram Erraqabi, Marlos C. Machado
, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio:
Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. UAI 2022: 641-651 - John Isak Texas Falk
, Carlo Ciliberto, Massimiliano Pontil:
Implicit kernel meta-learning using kernel integral forms. UAI 2022: 652-662 - Yassir Fathullah, Mark J. F. Gales:
Self-distribution distillation: efficient uncertainty estimation. UAI 2022: 663-673 - Jean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann:
Sequential algorithmic modification with test data reuse. UAI 2022: 674-684 - Sahil Garg, Umang Gupta, Yu Chen, Syamantak Datta Gupta, Yeshaya Adler, Anderson Schneider, Yuriy Nevmyvaka:
Estimating transfer entropy under long ranged dependencies. UAI 2022: 685-695 - Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes:
Mitigating statistical bias within differentially private synthetic data. UAI 2022: 696-705 - Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen:
Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programming. UAI 2022: 707-717 - Misha Glazunov, Apostolis Zarras:
Do Bayesian variational autoencoders know what they don't know? UAI 2022: 718-727 - Jinwoo Go, Tobin Isaac:
Robust expected information gain for optimal Bayesian experimental design using ambiguity sets. UAI 2022: 728-737 - Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen:
Efficient and transferable adversarial examples from bayesian neural networks. UAI 2022: 738-748 - Soumyajit Gupta, Gurpreet Singh, Raghu Bollapragada, Matthew Lease:
Learning a neural Pareto manifold extractor with constraints. UAI 2022: 749-758 - Ali Hasan, Khalil Elkhalil, Yuting Ng, João M. Pereira, Sina Farsiu, Jose H. Blanchet, Vahid Tarokh:
Modeling extremes with d-max-decreasing neural networks. UAI 2022: 759-768 - Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel:
Generalizing off-policy learning under sample selection bias. UAI 2022: 769-779 - Keyang He, Prashant Doshi, Bikramjit Banerjee:
Reinforcement learning in many-agent settings under partial observability. UAI 2022: 780-789 - Pashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen:
Variational multiple shooting for Bayesian ODEs with Gaussian processes. UAI 2022: 790-799 - Margot Herin, Patrice Perny, Nataliya Sokolovska:
Learning sparse representations of preferences within Choquet expected utility theory. UAI 2022: 800-810 - Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo:
Quadratic metric elicitation for fairness and beyond. UAI 2022: 811-821 - Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig:
Fast predictive uncertainty for classification with Bayesian deep networks. UAI 2022: 822-832 - Haruo Hosoya:
CIGMO: Categorical invariant representations in a deep generative framework. UAI 2022: 833-843 - Bingshan Hu, Nidhi Hegde:
Near-optimal Thompson sampling-based algorithms for differentially private stochastic bandits. UAI 2022: 844-852