Asia
Domes to Drones: Self-Supervised Active Triangulation for 3D Human Pose Reconstruction
In contrast, 3d pose estimation from a single image is ill-posed due to occlusion and depth ambiguities.
Achieving Domain-Independent Certified Robustness via Knowledge Continuity Alan Sun
These bounds are independent of domain modality, norms, and distribution.
Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction
Difan Zou, Pan Xu, Quanquan Gu
Figure 3: Ex represents (c)-(d) ConB.
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $\beta$-Divergences
Jeremias Knoblauch, Jack E. Jewson, Theodoros Damoulas
Neural Information Processing Systems http://nips.cc/
Fisher Efficient Inference of Intractable Models
Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen
We prove its consistency and show that the asymptotic variance ofitssolution canattaintheequality oftheefficiencybound undermild regularity conditions.
Alleviating Label Switching with Optimal Transport
Pierre Monteiller, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M. Solomon, Mikhail Yurochkin
Sampling and inference algorithms behave poorly as the number of modes increases, andthisproblem isonlyexacerbated inthiscontextsinceincreasing thenumber ofcomponents in the mixture model leads to a super-exponential increase in the number of modes of the posterior.
Mallows Models for Top-k Lists
Flavio Chierichetti, Anirban Dasgupta, Shahrzad Haddadan, Ravi Kumar, Silvio Lattanzi
The classic Mallows model is a widely-used tool to realize distributions on permutations.
Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity
Deepak Pathak, Christopher Lu, Trevor Darrell, Phillip Isola, Alexei A. Efros
Contemporary sensorimotor learning approaches typically start with anexisting complexagent (e.g., arobotic arm), which theylearn tocontrol. Limbs pass messages to their neighbors in this graph in order to coordinate behavior.