📢 17 papers by WASP PhD students, postdocs, supervisors and recruited researchers have been accepted at ICML, one of the premier conferences in machine learning.
The 41st International Conference on Machine Learning (ICML) will be held in Vienna, Austria, on July 21–27, 2024.
Accepted papers:
Anahita Baninajjar, Ahmed Rezine, and Amir Aminifar, "VNNs: Verification-Friendly Neural Networks with Hard Robustness Guarantees"
Daniel Gedon, Antonio H. Ribeiro, and Thomas B. Schön, "No double descent in principal component regression: A high-dimensional analysis"
Jan Gerken and Pan Kessel, "Emergent Equivariance in Deep Ensembles"
Alexandra Hotti, Oskar Kviman, Ricky Molén, Víctor Elvira, and Jens Lagergren, "Efficient Mixture Learning in Black-Box Variational Inference"
Carl Hvarfner, Erik Orm Hellsten, and Luigi Nardi, "Vanilla Bayesian Optimization Performs Great in High Dimensions"
Yassir Jedra, William Reveillard, Stefan Stojanovic, and Alexandre Proutiere, "Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery"
Arvi Jonnarth, Jie Zhao, and Michael Felsberg, "Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning"
Aleksandr Karakulev, Dave Zachariah, and Prashant Singh, "Adaptive Robust Learning using Latent Bernoulli Variables"
Rasmus Kjær Høier and Christopher Zach, "Two Tales of Single-Phase Contrastive Hebbian Learning"
Jaron Maene, Vincent Derkinderen, and Luc De Raedt, "On the Hardness of Probabilistic Neurosymbolic Learning"
Amir Mohammad Karimi Mamaghan, Panagiotis Tigas, Karl Johansson, Yarin Gal, Yashas Annadani, and Stefan Bauer, "Challenges and Considerations in the Evaluation of Bayesian Causal Discovery"
Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck, Andreas Robinson, and Cuong Le, "O$n$ Learning Deep O($n$)-Equivariant Hyperspheres"
Alfred Nilsson, Klas Wijk, Sai bharath chandra Gutha, Erik Englesson, Alexandra Hotti, Carlo Saccardi, Oskar Kviman, Jens Lagergren, Ricardo Vinuesa, and Hossein Azizpour, "Indirectly Parameterized Concrete Autoencoders"
Viktor Nilsson, Anirban Samaddar, Sandeep Madireddy, and Pierre Nyquist, "REMEDI: Corrective Transformations for Improved Neural Entropy Estimation"
Po-An Wang, Kaito Ariu, and Alexandre Proutiere, "On Universally Optimal Algorithms for A/B Testing"
Theodor Westny, Arman Mohammadi, Daniel Jung, and Erik Frisk, "Stability-Informed Initialization of Neural Ordinary Differential Equations"
Frederic Zheng and Alexandre Proutiere, "Conformal Prediction under Markovian Data"
See the ICML 2024 website for all accepted papers: https://lnkd.in/dQb57w4k
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[ICML] Int'l Conference on Machine Learning