Michael Christoph Gastpar

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We show that the recently proposed integer-forcing linear receiver provides an attractive approach to the problem of mitigating external interference in MIMO channels. The integer-forcing receiver proceeds by first decoding a set of full rank integer linear combinations of the data streams. The resulting full rank equations are then inverted to find the original data. By selecting equation coefficients in a direction that depends on both the interference space and the channel matrix, the impact of external

Download Citation Email Print Request Permissions Save to Project In this paper we study the problem of data exchange, where each node in the system has a number of linear combinations of the data packets. Communicating over a public channel, the goal is for all nodes to reconstruct the entire set of the data packets in minimal total number of bits exchanged over the channel. We present a novel divide and conquer based architecture that determines the number of bits each node should transmit. This along wit

Under the paradigm of caching, partial data are delivered before the actual requests of users are known. In this paper, this problem is modeled as a canonical distributed source coding problem with side information, where the side information represents th ...

We study a caching problem that resembles a lossy Gray–Wyner network: A source produces vector samples from a Gaussian distribution, but the user is interested in the samples of only one component. The encoder first sends a cache message without any knowle ...

Data-parallel SGD is the de facto algorithm for distributed optimization, especially for large scale machine learning. Despite its merits, communication bottleneck is one of its persistent issues. Most compression schemes to alleviate this either assume noiseless communication links, or fail to achieve good performance on practical tasks. In this paper, we close this gap and introduce LASER: LineAr CompreSsion in WirEless DistRibuted Optimization. LASER capitalizes on the inherent low-rank structure of grad

Information encoded in neuron ensembles has previously been hypothesized to be highly redundant, despite the apparent inefficiency of a redundant encoding system. The recent availability of intracortical, multi-electrode recordings has enabled the possibility of exploring how neuronal ensembles encode information as a whole. Applying concepts from information theory, we examined the redundancy of the target information encoded in both contralateral and ipsilateral hemispheres of the primary motor cortex (M1

Caching is technique that alleviates networks during peak hours by transmitting partial information before a request for any is made. We study this method in a lossy source coding setting with Gaussian databases. A good caching strategy minimizes the data ...

We consider the problem of source coding subject to a fidelity criterion for the Gray-Wyner network that connects a single source with two receivers via a common channel and two private channels. The pareto-optimal trade-offs between the sum-rate of the pr ...

Strong data processing inequalities (SDPI) are an important object of study in Information Theory and have been well studied for f-divergences. Universal upper and lower bounds have been provided along with several applications, connecting them to impossib ...

Attention-based transformers have been remarkably successful at modeling generative processes across various domains and modalities. In this paper, we study the behavior of transformers on data drawn from k(th)-order Markov processes, where the conditional distribution of the next symbol in a sequence depends on the previous k symbols observed. We observe a surprising phenomenon empirically which contradicts previous findings: when trained for sufficiently long, a transformer with a fixed depth and 1 head p

List-decoding for arbitrarily varying channels (AVCs) under state constraints is investigated. It is shown that rates within of the randomized coding capacity of AVCs with input-dependent state can be achieved under maximal error with list-decoding using l ...

In the distributed remote (CEO) source coding problem, many separate encoders observe independently noisy copies of an underlying source. The rate loss is the difference between the rate required in this distributed setting and the rate that would be requi ...

In this paper, we consider a cache aided network in which each user is assumed to have individual caches, while upon users’ requests, an update message is sent through a common link to all users. First, we formulate a general information theoretic setting ...

It is plausible to hypothesize that the spiking responses of certain neurons represent functions of the spiking signals of other neurons. A natural ensuing question concerns how to use experimental data to infer what kind of a function is being computed. M ...

This paper introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's mutual information ...

A major challenge in sparsity pattern estimation is that small modes are difficult to detect in the presence of noise. This problem is alleviated if one can observe samples from multiple realizations of the nonzero values for the same sparsity pattern. We will refer to this as “diversity”. Diversity comes at a price, however, since each new realization adds new unknown nonzero values, thus increasing uncertainty. In this paper, upper and lower bounds on joint sparsity pattern estimation are derived. These b

To reduce the network load during peak hours, servers deliver partial data to users during the off-peak time of the network before the actual requests are known, which is known as caching. This paper studies a single user caching problem in which the file ...

We consider a physical-layer network coding strat- egy for the random-access channel, based on compute-and- forward. When packets collide, it is possible to reliably recover a linear combination of the packets at the receiver. Over many rounds of transmiss ...

The successful design of sensor network architectures depends crucially on the structure of the sampling, observation, and communication processes. One of the most fundamental ques- tions concerns the sufficiency of discrete approximations in time, space, ...

The classical modulo-lattice construction of Erez et al. has been successfully applied to several coding problems under Gaussian noise, including coding for computation over multiple-access channels (MAC). For the latter problem, an alternative construction can be developed by extending a recently proposed nested linear code to Gaussian case. In this note, it is shown that using the nested linear code with judiciously chosen input distributions, the original compute-and-forward result is recovered and large

Michael Christoph Gastpar

Chattez avec Graph Search

Mitigating interference with integer-forcing architectures

Deterministic algorithm for the cooperative data exchange problem

Information-Theoretic Caching: Sequential Coding for Computing

Caching Gaussians: Minimizing Total Correlation on the Gray–Wyner Network

LASER: Linear Compression in Wireless Distributed Optimization

Redundant information encoding in primary motor cortex during motor tasks

Caching of Bivariate Gaussians with Non-Uniform Preference Probabilities

The Gaussian lossy Gray-Wyner network

Properties of the Strong Data Processing Constant for Rényi Divergence

Transformers on Markov Data: Constant Depth Suffices

List-Decoding for the Arbitrarily Varying Channel Under State Constraints

The Price of Distributed: Rate Loss in the CEO Problem

Information-Theoretic Caching: The Multi-User Case

Function Identification in Neuron Populations via Information Bottleneck

Quantifying high-order interdependencies via multivariate extensions of the mutual information

On the role of diversity in sparsity estimation

Successive Refinement to Caching for Dynamic Content

Physical-layer Network Coding on the Random-access Channel

Sensing and communication with and without bits

Compute-and-Forward using nested linear codes for the Gaussian MAC