
Distributed Mean Estimation with Optimal Error Bounds
Motivated by applications to distributed optimization and machine learni...
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Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent
Machine learning has made tremendous progress in recent years, with mode...
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XGAN: Unsupervised ImagetoImage Translation for ManytoMany Mappings
Style transfer usually refers to the task of applying color and texture ...
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Optimizing Expectation with Guarantees in POMDPs (Technical Report)
A standard objective in partiallyobservable Markov decision processes (...
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Extrapolation and learning equations
In classical machine learning, regression is treated as a black box proc...
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Instrumenting an SMT Solver to Solve Hybrid Network Reachability Problems
PDDL+ planning has its semantics rooted in hybrid automata (HA) and rece...
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Streaming Algorithm for Euler Characteristic Curves of Multidimensional Images
We present an efficient algorithm to compute Euler characteristic curves...
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Semiparametric energybased probabilistic models
Probabilistic models can be defined by an energy function, where the pro...
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Automatic Generation of Alternative Starting Positions for Simple Traditional Board Games
Simple board games, like TicTacToe and CONNECT4, play an important ro...
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Multitask and Lifelong Learning of Kernels
We consider a problem of learning kernels for use in SVM classification ...
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MultiTask Learning with Labeled and Unlabeled Tasks
In multitask learning, a learner is given a collection of prediction ta...
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Conditional Risk Minimization for Stochastic Processes
We study the task of learning from noni.i.d. data. In particular, we ai...
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Seed, Expand and Constrain: Three Principles for WeaklySupervised Image Segmentation
We introduce a new loss function for the weaklysupervised training of s...
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Learning to Transfer Privileged Information
We introduce a learning framework called learning using privileged infor...
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DifferentiallyPrivate Logistic Regression for Detecting MultipleSNP Association in GWAS Databases
Following the publication of an attack on genomewide association studie...
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Predicting the Future Behavior of a TimeVarying Probability Distribution
We study the problem of predicting the future, though only in the probab...
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Generalized RiskAversion in Stochastic MultiArmed Bandits
We consider the problem of minimizing the regret in stochastic multiarm...
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Domain Adaptation of Majority Votes via Perturbed Variationbased Label Transfer
We tackle the PACBayesian Domain Adaptation (DA) problem. This arrives ...
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Identifying Reliable Annotations for Large Scale Image Segmentation
Challenging computer vision tasks, in particular semantic image segmenta...
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Total variation on a tree
We consider the problem of minimizing the continuous valued total variat...
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Potts model, parametric maxflow and ksubmodular functions
The problem of minimizing the Potts energy function frequently occurs in...
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Combinatorial Gradient Fields for 2D Images with Empirically Convergent Separatrices
This paper proposes an efficient probabilistic method that computes comb...
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Natural images from the birthplace of the human eye
Here we introduce a database of calibrated natural images publicly avail...
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On the treewidth of triangulated 3manifolds
In graph theory, as well as in 3manifold topology, there exist several ...
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Causalitybased Model Checking
Model checking is usually based on a comprehensive traversal of the stat...
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A Proof of the Orbit Conjecture for Flipping EdgeLabelled Triangulations
Given a triangulation of a point set in the plane, a flip deletes an edg...
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Efficient Algorithms for Checking Fast Termination in VASS
Vector Addition Systems with States (VASS) consists of a finite state sp...
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Towards Practical Conditional Risk Minimization
We study conditional risk minimization (CRM), i.e. the problem of learni...
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Quantitative Analysis of Smart Contracts
Smart contracts are computer programs that are executed by a network of ...
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DataBright: Towards a Global Exchange for Decentralized Data Ownership and Trusted Computation
It is safe to assume that, for the foreseeable future, machine learning,...
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Model compression via distillation and quantization
Deep neural networks (DNNs) continue to make significant advances, solvi...
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Testing the complexity of a valued CSP language
A Valued Constraint Satisfaction Problem (VCSP) provides a common framew...
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InfiniteDuration PoormanBidding Games
In twoplayer games on graphs, the players move a token through a graph ...
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Algorithms and Conditional Lower Bounds for Planning Problems
We consider planning problems for graphs, Markov decision processes (MDP...
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Computational Approaches for Stochastic Shortest Path on Succinct MDPs
We consider the stochastic shortest path (SSP) problem for succinct Mark...
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Efficient Algorithms for Asymptotic Bounds on Termination Time in VASS
Vector Addition Systems with States (VASS) provide a wellknown and fund...
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Secure Credit Reporting on the Blockchain
We present a secure approach for maintaining and reporting credit histor...
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A note on belief structures and Sapproximation spaces
We study relations between evidence theory and Sapproximation spaces. B...
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MAP inference via BlockCoordinate FrankWolfe Algorithm
We present a new proximal bundle method for MaximumAPosteriori (MAP) i...
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New Approaches for AlmostSure Termination of Probabilistic Programs
We study the almostsure termination problem for probabilistic programs....
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Detecting Visual Relationships Using Box Attention
In this paper we propose a new model for detecting visual relationships....
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The Convergence of Sparsified Gradient Methods
Distributed training of massive machine learning models, in particular d...
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Why ExtensionBased Proofs Fail
We prove that a class of fundamental shared memory tasks are not amenabl...
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Back to square one: probabilistic trajectory forecasting without bells and whistles
We introduce a spatiotemporal convolutional neural network model for tr...
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The Crossing Tverberg Theorem
Tverberg's theorem is one of the cornerstones of discrete geometry. It s...
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Compositional Analysis for AlmostSure Termination of Probabilistic Programs
In this work, we consider the almostsure termination problem for probab...
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Robust Learning from Untrusted Sources
Modern machine learning methods often require more data for training tha...
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Cost Analysis of Nondeterministic Probabilistic Programs
We consider the problem of expected cost analysis over nondeterministic ...
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Token Swapping on Trees
The input to the token swapping problem is a graph with vertices v_1, v_...
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Topological Data Analysis in Information Space
Various kinds of data are routinely represented as discrete probability ...
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Institute of Science and Technology Austria
The Institute of Science and Technology Austria, commonly known as IST Austria, is an international research institute in natural and mathematical sciences, located in Maria Gugging, Klosterneuburg, 20 km northwest of the Austrian capital of Vienna.